{
 "cells": [
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   },
   "source": [
    "# Exercise 11) Policy Gradients"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "grade_id": "cell-e732f039d63130ba",
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   "source": [
    "In this exercise we will have a look at policy gradients. \n",
    "The theory of policy gradients applies to function approximators that decide on which action to choose. \n",
    "The function approximators we met in the past were employed to estimate the (action) value function. \n",
    "Since their task was to judge the quality of the current situation they are often referred to as \"critics\". \n",
    "In contrary, we can also use a function approximator to directly choose an action; we call these \"actors\". \n",
    "Why should we do that if we made it work with nothing more than a critic? \n",
    "Because this will finally allow us to make use of contiuous action spaces! Eureka!\n",
    "\n",
    "In this exercise we will use a new `gym` environment `LunarLanderContinuous-v3`.\n",
    "To run this environment please make sure to have `Box2D` installed: `pip install Box2D`.\n",
    "\n",
    "![](https://images.squarespace-cdn.com/content/v1/59e0d6f0197aea1a0abc8016/1507938542206-41S6K9T97YETKEHP0PQF/ke17ZwdGBToddI8pDm48kMR1yAHb8bPoH1-OdajP2rZZw-zPPgdn4jUwVcJE1ZvWQUxwkmyExglNqGp0IvTJZUJFbgE-7XRK3dMEBRBhUpyDg3tXaPHS4cFkn9Bnm-emI0BDr_E-XKAFKqWrx68ZVlLyhCgVi_FJvVMH7mHrc18/lunar_lander_success_example.gif?format=500w)\n",
    "\n",
    "Source: https://www.billyvreeland.com/portfolio/2017/1013/solving-openai-gym-nm4yz\n",
    "\n",
    "The main task is to land the LunarLander in the landing zone.\n",
    "An accident-free landing is defined by both legs coming into  ground contact with moderate velocity.\n",
    "We are dealing with a continuous state and action space as defined below.\n",
    "Please notice that the control functions for main and side engines contain a dead zone in which the engines are inactive.\n",
    "The reward is mainly defined depending on whether the landing procedure is successful (+100) or not (-100).\n",
    "Firing the main engine gives a small negative reward. \n",
    "The problem is solved if a return of at least 200 is reached. \n",
    "For more information see https://gymnasium.farama.org/environments/box2d/lunar_lander/.\n",
    "\n"
   ]
  },
  {
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   "source": [
    "\n",
    "\\begin{align}\n",
    "\\text{state}&=\n",
    "\\begin{bmatrix}\n",
    "p_x\\\\\n",
    "p_y\\\\\n",
    "v_x\\\\\n",
    "v_y\\\\\n",
    "\\varphi\\\\\n",
    "20 \\, \\omega\\\\\n",
    "1 \\text{ if left leg has ground contact, else } 0\\\\\n",
    "1 \\text{ if right leg has ground contact, else } 0\\\\\n",
    "\\end{bmatrix}\n",
    "\\\\\n",
    "\\text{action}&=\n",
    "\\begin{bmatrix}\n",
    "\\text{main engine: } [-1, 0] \\rightarrow \\text{off}, ]0, 1] \\rightarrow [50 \\, \\%, 100 \\, \\%] \\text{ of available power}\\\\\n",
    "\\text{side engines: } [-1, -0.5] \\rightarrow [50 \\, \\%, 100 \\, \\%] \\text{ of available left engine power}, [0.5, 1] \\rightarrow [50 \\, \\%, 100 \\, \\%] \\text{ of available right engine power}\\\\\n",
    "\\end{bmatrix}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-cb8f30d3aea6982a",
     "locked": true,
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     "task": false
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   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import gymnasium as gym\n",
    "from tqdm.notebook import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.kernel_approximation import RBFSampler\n",
    "import sklearn.pipeline\n",
    "import sklearn.preprocessing\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-8986527608544bb1",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "env = gym.make(\"LunarLander-v3\",\n",
    "                continuous=True,\n",
    "              render_mode = \"human\")\n",
    "\n",
    "state = env.reset()\n",
    "while True:\n",
    "    state, reward, terminated, truncated, _ = env.step(env.action_space.sample())\n",
    "    done = terminated or truncated\n",
    "\n",
    "    if done:\n",
    "        break\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-a5be36d9e2de2982",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 1) Monte Carlo Policy Gradient\n",
    "Write a REINFORCE algorithm."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "grade_id": "cell-5fef942298a07621",
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    },
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Execute the following cell to fit the featurizer using RBFSampler, like already learned in the last exercises. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
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     "grade_id": "cell-6a414b0a2359c70d",
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     "solution": false,
     "task": false
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    "pycharm": {
     "is_executing": true
    }
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       "  0%|          | 0/1000 [00:00<?, ?it/s]"
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   "source": [
    "env = gym.make(\"LunarLander-v3\",\n",
    "                continuous=True)\n",
    "state_array = []\n",
    "state = env.reset()\n",
    "\n",
    "for i in tqdm(range(1000)):\n",
    "    state, _ = env.reset()\n",
    "    while True:\n",
    "        state, reward, terminated, truncated, _ = env.step(env.action_space.sample())\n",
    "        done = terminated or truncated\n",
    "        state_array.append(state)\n",
    "\n",
    "        if done:\n",
    "            break\n",
    "\n",
    "state_array = np.array(state_array)\n",
    "\n",
    "featurizer = sklearn.pipeline.make_pipeline(\n",
    "    sklearn.preprocessing.StandardScaler(),\n",
    "    sklearn.pipeline.FeatureUnion([\n",
    "    (\"rbf0\", RBFSampler(gamma=5.0, n_components = 1000)),\n",
    "    (\"rbf1\", RBFSampler(gamma=2.0, n_components = 1000)),\n",
    "    (\"rbf2\", RBFSampler(gamma=1.0, n_components = 1000)),\n",
    "    (\"rbf3\", RBFSampler(gamma=0.5, n_components = 1000)),\n",
    "    ]),\n",
    "    sklearn.preprocessing.StandardScaler()\n",
    ")\n",
    "\n",
    "_ = featurizer.fit(state_array)\n",
    "env.close()\n"
   ]
  },
  {
   "cell_type": "markdown",
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    "nbgrader": {
     "grade": false,
     "grade_id": "cell-3c04ca9fbfe07902",
     "locked": true,
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     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Use the following cell to define the function approximators for the policy.\n",
    "As seen in Algo.12.1 we need to calculate $\\nabla_\\theta \\mathrm{ln}\\,\\pi(u_k | x_k, \\theta)$.\n",
    "$\\pi$ is herein defined as the normal distribution : \n",
    "\\begin{align}\n",
    "\\pi(u_k | x_k, \\theta) & = \\frac{\\mathrm{exp} \\left( {-\\frac{1}{2} (u_k - \\mu_\\theta(x_k))^\\mathrm{T} \\mathbf{\\Sigma}^{-1}_\\theta(x_k) (u_k - \\mu_\\theta(x_k))} \\right)}{\\sqrt{(2\\pi)^p \\mathrm{det}(\\mathbf{\\Sigma}_\\theta(x_k))}},\\\\\n",
    "\\text{with}\\hspace{1em} p & = \\mathrm{dim}(u_k).\n",
    "\\end{align}\n",
    "\n",
    "Extend `loglikelyhoodGaussian` such that it returns $\\mathrm{ln}\\,\\pi(u_k | x_k, \\theta)$! \n",
    "Use the numpy equivalent `PyTorch` functions (e.g. `torch.linalg.inv()`).\n",
    "`PyTorch` functions are differentiable and can therefore be  used to calculate $\\nabla_\\theta \\mathrm{ln}\\,\\pi(u_k | x_k, \\theta)$.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "class PolicyNetwork(nn.Module):\n",
    "\n",
    "    def __init__(self, input_dim, action_space_dim):\n",
    "        super(PolicyNetwork, self).__init__()\n",
    "        self.fc1 = nn.Linear(input_dim, 400)\n",
    "        self.fc2 = nn.Linear(400, 400)\n",
    "        self.fc3_mu = nn.Linear(400, action_space_dim)\n",
    "        self.fc3_sigma = nn.Linear(400, action_space_dim)\n",
    "\n",
    "    def forward(self, x):\n",
    "        \"\"\"Predict the parameters of the stochastic distribution from which the action\n",
    "        is sampled.\n",
    "        \"\"\"\n",
    "        x = F.leaky_relu(self.fc1(x), 0.1)\n",
    "        x = F.leaky_relu(self.fc2(x), 0.1)\n",
    "\n",
    "        mu_out = self.fc3_mu(x)\n",
    "        mu_out = torch.clip(mu_out, -1, 1)[0]\n",
    "\n",
    "        sigma_out = F.softplus(self.fc3_sigma(x))\n",
    "        sigma_out = torch.mm(sigma_out, torch.tensor([[0.01, 0], [0, 0.1]]))\n",
    "        sigma_out = torch.clip(sigma_out, 1e-4, 1)\n",
    "        sigma_out = torch.diag_embed(sigma_out[0])\n",
    "\n",
    "        return mu_out, sigma_out\n",
    "\n",
    "\n",
    "def loglikelihood_gaussian(u, arg_mu, arg_sigma):\n",
    "    \"\"\"Evaluate the loglikelihood of the multivariate gaussian.\n",
    "    \n",
    "    Args:\n",
    "        u: Where to evaluate the loglikelihood of the gaussian. In our case, this is\n",
    "            the action whose likelihood we are evaluating.\n",
    "        arg_mu: The mean vector of the gaussian distribution\n",
    "        arg_sigma: The covariance matrix of the gaussian distribution\n",
    "    \"\"\"\n",
    "    u = u.float()\n",
    "    arg_mu = arg_mu.float()\n",
    "    arg_sigma = arg_sigma.float()\n",
    "    \n",
    "    u_min_mu = u - arg_mu\n",
    "    u_min_mu_col = u_min_mu.unsqueeze(1)\n",
    "    \n",
    "    quadratic_term = u_min_mu_col.t().mm(torch.inverse(arg_sigma)).mm(u_min_mu_col)\n",
    "    log_det_sigma = torch.logdet(arg_sigma)\n",
    "    \n",
    "    dim = u.size(0)\n",
    "    constant_term = dim * torch.log(torch.tensor(2.0 * np.pi))\n",
    "    log_likelihood = -0.5 * (constant_term + log_det_sigma + quadratic_term)\n",
    "\n",
    "    return log_likelihood.squeeze()  # Ensure it's a scalar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-451a7f093f5186bb",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    }
   },
   "outputs": [],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True)\n",
    "\n",
    "state = np.reshape(env.reset()[0], (1, -1))\n",
    "feature_state = featurizer.transform(state)\n",
    "input_dim = feature_state.shape[1]\n",
    "action_space_dim = len(env.action_space.sample())\n",
    "\n",
    "policy = PolicyNetwork(input_dim, action_space_dim)\n",
    "\n",
    "# Regularization; downscaling of the network parameters to prevent divergence\n",
    "with torch.no_grad():\n",
    "    for param in policy.parameters():\n",
    "        param.mul_(0.4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-ed46e45053d3ffe3",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "Use the following template to write a REINFORCE algorithm.\n",
    "This time the Adam (adaptive moment estimation) optimizer is used, which is an enhanced SGD optimizer.\n",
    "For more information on the optimizer, see https://arxiv.org/abs/1412.6980."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def interact(state, policy, deterministic, featurizer):\n",
    "    \"\"\"Interact with the environment to get to the next state.\n",
    "    \n",
    "    Args:\n",
    "        state: The current state of the environment\n",
    "        policy: The model that returns the mean and covariance matrix of the policy distribution\n",
    "        deterministic: Whether to choose actions randomly or use the mean\n",
    "        featurizer: The featurizer for state preprocessing\n",
    "\n",
    "    Returns:\n",
    "        next_state: The following state of the environment after the interaction\n",
    "        reward: The reward for the interaction\n",
    "        done: Whether the current episode is finished\n",
    "        action: The chosen action\n",
    "        mu: The mean vector of the policy distribution\n",
    "        sigma: The covariance matrix of the policy distribution\n",
    "    \"\"\"\n",
    "    feature_state = torch.tensor(featurizer.transform(state), dtype=torch.float32)\n",
    "    mu, sigma = policy(feature_state)\n",
    "\n",
    "    if deterministic:\n",
    "        action = mu.detach().numpy().ravel()\n",
    "    else:\n",
    "        action = np.random.multivariate_normal(mean=mu.detach().numpy().ravel(), cov=sigma.detach().numpy())\n",
    "\n",
    "    next_state, reward, terminated, truncated, _ = env.step(action)\n",
    "    done = terminated or truncated\n",
    "\n",
    "    return next_state, reward, done, action, mu, sigma\n",
    "\n",
    "def gather_experience(policy, featurizer, max_episode_len=1000):\n",
    "    \"\"\"Simulates a full episode and returns the gathered data.\n",
    "\n",
    "    Args:\n",
    "        policy: The model that returns the mean and covariance matrix of the policy distribution\n",
    "        featurizer: The featurizer for state preprocessing\n",
    "        max_episode_len: The number of steps at which the episode is terminated automatically\n",
    "\n",
    "    Returns:\n",
    "        states: The states visited in the episode\n",
    "        actions: The actions applied in the epsiode\n",
    "        rewards: The rewards gathered in the episode\n",
    "        probs_log: The loglikelihood values for the chosen actions\n",
    "        accumulated_rewards: The sum of rewards over the episode\n",
    "    \"\"\"\n",
    "    accumulated_rewards = 0\n",
    "\n",
    "    states = []\n",
    "    actions = []\n",
    "    rewards = []\n",
    "    probs_log = []\n",
    "\n",
    "    state, _ = env.reset()\n",
    "    state = torch.tensor(state.reshape(1, -1), dtype=torch.float32)\n",
    "\n",
    "    for _ in range(max_episode_len):  # Limiting each episode to a maximum length\n",
    "        next_state, reward, done, action, mu, sigma = interact(state, policy, False, featurizer)\n",
    "\n",
    "        states.append(state)\n",
    "        actions.append(torch.tensor(action, dtype=torch.float32))\n",
    "        rewards.append(reward)\n",
    "        probs_log.append(loglikelihood_gaussian(torch.tensor(action, dtype=torch.float32), mu, sigma))\n",
    "\n",
    "        accumulated_rewards += reward\n",
    "        state = torch.tensor(next_state.reshape(1, -1), dtype=torch.float32)\n",
    "\n",
    "        if done:\n",
    "            break\n",
    "    \n",
    "    return states, actions, rewards, probs_log, accumulated_rewards\n",
    "\n",
    "\n",
    "def compute_returns(states, rewards, gamma):\n",
    "    \"\"\"Compute the returns based on the gathered rewards.\"\"\"\n",
    "    g_returns = []\n",
    "    for t in range(len(states)):\n",
    "        g_t = 0\n",
    "        pw = 0\n",
    "        for r in rewards[t:]:\n",
    "            g_t = g_t + gamma**pw * r\n",
    "            pw = pw + 1\n",
    "        #NOTE: The following line is closer to the lecture pseudocode, but it seems to be working worse\n",
    "        #g_returns.append(g_t*(gamma**t))\n",
    "        g_returns.append(g_t)\n",
    "    return torch.tensor(g_returns, dtype=torch.float32)\n",
    "\n",
    "\n",
    "def learn(states, rewards, gamma, probs_log, optimizer):\n",
    "    \"\"\"Learn from the gathered experience.\"\"\"\n",
    "\n",
    "    g_returns = compute_returns(states, rewards, gamma)\n",
    "\n",
    "    # Calculate Policy Loss\n",
    "    policy_loss = 0\n",
    "    for log_prob, g_t in zip(probs_log, g_returns):\n",
    "        policy_loss = policy_loss - log_prob * g_t\n",
    "\n",
    "    # Update Policy\n",
    "    optimizer.zero_grad()\n",
    "    policy_loss.backward()\n",
    "    optimizer.step()\n",
    "\n",
    "    return policy_loss.item()\n"
   ]
  },
  {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mKeyboardInterrupt\u001b[39m                         Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[28]\u001b[39m\u001b[32m, line 11\u001b[39m\n\u001b[32m      7\u001b[39m nb_episodes = \u001b[32m5000\u001b[39m\n\u001b[32m      9\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m tqdm(\u001b[38;5;28mrange\u001b[39m(nb_episodes)):\n\u001b[32m---> \u001b[39m\u001b[32m11\u001b[39m     states, actions, rewards, probs_log, accumulated_rewards = \u001b[43mgather_experience\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpolicy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfeaturizer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     13\u001b[39m     _ = learn(states, rewards, gamma, probs_log, optimizer)\n\u001b[32m     15\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m j % \u001b[32m250\u001b[39m == \u001b[32m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m j != \u001b[32m0\u001b[39m:\n",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[27]\u001b[39m\u001b[32m, line 57\u001b[39m, in \u001b[36mgather_experience\u001b[39m\u001b[34m(policy, featurizer, max_episode_len)\u001b[39m\n\u001b[32m     54\u001b[39m state = torch.tensor(state.reshape(\u001b[32m1\u001b[39m, -\u001b[32m1\u001b[39m), dtype=torch.float32)\n\u001b[32m     56\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(max_episode_len):  \u001b[38;5;66;03m# Limiting each episode to a maximum length\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m57\u001b[39m     next_state, reward, done, action, mu, sigma = \u001b[43minteract\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpolicy\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfeaturizer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m     59\u001b[39m     states.append(state)\n\u001b[32m     60\u001b[39m     actions.append(torch.tensor(action, dtype=torch.float32))\n",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[27]\u001b[39m\u001b[32m, line 18\u001b[39m, in \u001b[36minteract\u001b[39m\u001b[34m(state, policy, deterministic, featurizer)\u001b[39m\n\u001b[32m      1\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34minteract\u001b[39m(state, policy, deterministic, featurizer):\n\u001b[32m      2\u001b[39m \u001b[38;5;250m    \u001b[39m\u001b[33;03m\"\"\"Interact with the environment to get to the next state.\u001b[39;00m\n\u001b[32m      3\u001b[39m \n\u001b[32m      4\u001b[39m \u001b[33;03m    Args:\u001b[39;00m\n\u001b[32m   (...)\u001b[39m\u001b[32m     16\u001b[39m \u001b[33;03m        sigma: The covariance matrix of the policy distribution\u001b[39;00m\n\u001b[32m     17\u001b[39m \u001b[33;03m    \"\"\"\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m18\u001b[39m     feature_state = torch.tensor(\u001b[43mfeaturizer\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m)\u001b[49m, dtype=torch.float32)\n\u001b[32m     19\u001b[39m     mu, sigma = policy(feature_state)\n\u001b[32m     21\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m deterministic:\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\pipeline.py:1092\u001b[39m, in \u001b[36mPipeline.transform\u001b[39m\u001b[34m(self, X, **params)\u001b[39m\n\u001b[32m   1090\u001b[39m Xt = X\n\u001b[32m   1091\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m _, name, transform \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m._iter():\n\u001b[32m-> \u001b[39m\u001b[32m1092\u001b[39m     Xt = \u001b[43mtransform\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mXt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mrouted_params\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1093\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m Xt\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\utils\\_set_output.py:319\u001b[39m, in \u001b[36m_wrap_method_output.<locals>.wrapped\u001b[39m\u001b[34m(self, X, *args, **kwargs)\u001b[39m\n\u001b[32m    317\u001b[39m \u001b[38;5;129m@wraps\u001b[39m(f)\n\u001b[32m    318\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mwrapped\u001b[39m(\u001b[38;5;28mself\u001b[39m, X, *args, **kwargs):\n\u001b[32m--> \u001b[39m\u001b[32m319\u001b[39m     data_to_wrap = \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    320\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data_to_wrap, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[32m    321\u001b[39m         \u001b[38;5;66;03m# only wrap the first output for cross decomposition\u001b[39;00m\n\u001b[32m    322\u001b[39m         return_tuple = (\n\u001b[32m    323\u001b[39m             _wrap_data_with_container(method, data_to_wrap[\u001b[32m0\u001b[39m], X, \u001b[38;5;28mself\u001b[39m),\n\u001b[32m    324\u001b[39m             *data_to_wrap[\u001b[32m1\u001b[39m:],\n\u001b[32m    325\u001b[39m         )\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\pipeline.py:2041\u001b[39m, in \u001b[36mFeatureUnion.transform\u001b[39m\u001b[34m(self, X, **params)\u001b[39m\n\u001b[32m   2038\u001b[39m     \u001b[38;5;28;01mfor\u001b[39;00m name, _ \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m.transformer_list:\n\u001b[32m   2039\u001b[39m         routed_params[name] = Bunch(transform={})\n\u001b[32m-> \u001b[39m\u001b[32m2041\u001b[39m Xs = \u001b[43mParallel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mn_jobs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m   2042\u001b[39m \u001b[43m    \u001b[49m\u001b[43mdelayed\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_transform_one\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrans\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparams\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrouted_params\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   2043\u001b[39m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtrans\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mweight\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_iter\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   2044\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   2045\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m Xs:\n\u001b[32m   2046\u001b[39m     \u001b[38;5;66;03m# All transformers are None\u001b[39;00m\n\u001b[32m   2047\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m np.zeros((X.shape[\u001b[32m0\u001b[39m], \u001b[32m0\u001b[39m))\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\utils\\parallel.py:77\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m     72\u001b[39m config = get_config()\n\u001b[32m     73\u001b[39m iterable_with_config = (\n\u001b[32m     74\u001b[39m     (_with_config(delayed_func, config), args, kwargs)\n\u001b[32m     75\u001b[39m     \u001b[38;5;28;01mfor\u001b[39;00m delayed_func, args, kwargs \u001b[38;5;129;01min\u001b[39;00m iterable\n\u001b[32m     76\u001b[39m )\n\u001b[32m---> \u001b[39m\u001b[32m77\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m.\u001b[49m\u001b[34;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43miterable_with_config\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\joblib\\parallel.py:1918\u001b[39m, in \u001b[36mParallel.__call__\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m   1916\u001b[39m     output = \u001b[38;5;28mself\u001b[39m._get_sequential_output(iterable)\n\u001b[32m   1917\u001b[39m     \u001b[38;5;28mnext\u001b[39m(output)\n\u001b[32m-> \u001b[39m\u001b[32m1918\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m output \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.return_generator \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43moutput\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1920\u001b[39m \u001b[38;5;66;03m# Let's create an ID that uniquely identifies the current call. If the\u001b[39;00m\n\u001b[32m   1921\u001b[39m \u001b[38;5;66;03m# call is interrupted early and that the same instance is immediately\u001b[39;00m\n\u001b[32m   1922\u001b[39m \u001b[38;5;66;03m# re-used, this id will be used to prevent workers that were\u001b[39;00m\n\u001b[32m   1923\u001b[39m \u001b[38;5;66;03m# concurrently finalizing a task from the previous call to run the\u001b[39;00m\n\u001b[32m   1924\u001b[39m \u001b[38;5;66;03m# callback.\u001b[39;00m\n\u001b[32m   1925\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m._lock:\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\joblib\\parallel.py:1847\u001b[39m, in \u001b[36mParallel._get_sequential_output\u001b[39m\u001b[34m(self, iterable)\u001b[39m\n\u001b[32m   1845\u001b[39m \u001b[38;5;28mself\u001b[39m.n_dispatched_batches += \u001b[32m1\u001b[39m\n\u001b[32m   1846\u001b[39m \u001b[38;5;28mself\u001b[39m.n_dispatched_tasks += \u001b[32m1\u001b[39m\n\u001b[32m-> \u001b[39m\u001b[32m1847\u001b[39m res = \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1848\u001b[39m \u001b[38;5;28mself\u001b[39m.n_completed_tasks += \u001b[32m1\u001b[39m\n\u001b[32m   1849\u001b[39m \u001b[38;5;28mself\u001b[39m.print_progress()\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\utils\\parallel.py:139\u001b[39m, in \u001b[36m_FuncWrapper.__call__\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m    137\u001b[39m     config = {}\n\u001b[32m    138\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m config_context(**config):\n\u001b[32m--> \u001b[39m\u001b[32m139\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfunction\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\pipeline.py:1531\u001b[39m, in \u001b[36m_transform_one\u001b[39m\u001b[34m(transformer, X, y, weight, params)\u001b[39m\n\u001b[32m   1509\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_transform_one\u001b[39m(transformer, X, y, weight, params=\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[32m   1510\u001b[39m \u001b[38;5;250m    \u001b[39m\u001b[33;03m\"\"\"Call transform and apply weight to output.\u001b[39;00m\n\u001b[32m   1511\u001b[39m \n\u001b[32m   1512\u001b[39m \u001b[33;03m    Parameters\u001b[39;00m\n\u001b[32m   (...)\u001b[39m\u001b[32m   1529\u001b[39m \u001b[33;03m        This should be of the form ``process_routing()[\"step_name\"]``.\u001b[39;00m\n\u001b[32m   1530\u001b[39m \u001b[33;03m    \"\"\"\u001b[39;00m\n\u001b[32m-> \u001b[39m\u001b[32m1531\u001b[39m     res = \u001b[43mtransformer\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mparams\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   1532\u001b[39m     \u001b[38;5;66;03m# if we have a weight for this transformer, multiply output\u001b[39;00m\n\u001b[32m   1533\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m weight \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\utils\\_set_output.py:319\u001b[39m, in \u001b[36m_wrap_method_output.<locals>.wrapped\u001b[39m\u001b[34m(self, X, *args, **kwargs)\u001b[39m\n\u001b[32m    317\u001b[39m \u001b[38;5;129m@wraps\u001b[39m(f)\n\u001b[32m    318\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mwrapped\u001b[39m(\u001b[38;5;28mself\u001b[39m, X, *args, **kwargs):\n\u001b[32m--> \u001b[39m\u001b[32m319\u001b[39m     data_to_wrap = \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    320\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data_to_wrap, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[32m    321\u001b[39m         \u001b[38;5;66;03m# only wrap the first output for cross decomposition\u001b[39;00m\n\u001b[32m    322\u001b[39m         return_tuple = (\n\u001b[32m    323\u001b[39m             _wrap_data_with_container(method, data_to_wrap[\u001b[32m0\u001b[39m], X, \u001b[38;5;28mself\u001b[39m),\n\u001b[32m    324\u001b[39m             *data_to_wrap[\u001b[32m1\u001b[39m:],\n\u001b[32m    325\u001b[39m         )\n",
      "\u001b[36mFile \u001b[39m\u001b[32mc:\\Users\\Ali Abdelwanis\\anaconda3\\envs\\RL_course_py12\\Lib\\site-packages\\sklearn\\kernel_approximation.py:406\u001b[39m, in \u001b[36mRBFSampler.transform\u001b[39m\u001b[34m(self, X)\u001b[39m\n\u001b[32m    404\u001b[39m projection = safe_sparse_dot(X, \u001b[38;5;28mself\u001b[39m.random_weights_)\n\u001b[32m    405\u001b[39m projection += \u001b[38;5;28mself\u001b[39m.random_offset_\n\u001b[32m--> \u001b[39m\u001b[32m406\u001b[39m \u001b[43mnp\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcos\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprojection\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprojection\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    407\u001b[39m projection *= (\u001b[32m2.0\u001b[39m / \u001b[38;5;28mself\u001b[39m.n_components) ** \u001b[32m0.5\u001b[39m\n\u001b[32m    408\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m projection\n",
      "\u001b[31mKeyboardInterrupt\u001b[39m: "
     ]
    }
   ],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True, render_mode=\"rgb_array\")\n",
    "return_history = []\n",
    "\n",
    "alpha_policy = 1e-5\n",
    "optimizer = torch.optim.Adam(policy.parameters(), lr=alpha_policy)\n",
    "gamma = 0.99\n",
    "nb_episodes = 5000\n",
    "\n",
    "for j in tqdm(range(nb_episodes)):\n",
    "\n",
    "    states, actions, rewards, probs_log, accumulated_rewards = gather_experience(policy, featurizer)\n",
    "\n",
    "    _ = learn(states, rewards, gamma, probs_log, optimizer)\n",
    "\n",
    "    if j % 250 == 0 and j != 0:\n",
    "        plt.plot(return_history, label='Return')\n",
    "        plt.plot(pd.Series(return_history).rolling(10).mean(), label='MA')\n",
    "        plt.xlabel('episode')\n",
    "        plt.ylabel('return')\n",
    "        plt.grid(True)\n",
    "        _ = plt.legend()\n",
    "        plt.show()\n",
    "    return_history.append(accumulated_rewards)\n",
    "    \n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-10ea9f6de0129a23",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Plot the learning curve of the training process!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-9c960043e350900a",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "plt.plot(return_history, label='Return')\n",
    "plt.plot(pd.Series(return_history, name='reward_history').rolling(10).mean(), label='MA')\n",
    "plt.xlabel('episode')\n",
    "plt.ylabel('return')\n",
    "plt.grid(True)\n",
    "_=plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-88ab1f013663dfea",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "### Execution\n",
    "\n",
    "Use `deterministic` to choose between deterministic execution (applying $\\mu$ directly) or taking the stochastic action by sampling from the normal distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-5eaa6be280fc63bb",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a13de89a8b754c1d859dcbcde1d1c668",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode 0, Total Reward: -45.68870759940652\n",
      "Episode 1, Total Reward: -115.50172777607092\n",
      "Episode 2, Total Reward: -142.0701623081274\n",
      "Episode 3, Total Reward: -261.159549663965\n",
      "Episode 4, Total Reward: -115.42796267899337\n",
      "Episode 5, Total Reward: -119.86797078306002\n",
      "Episode 6, Total Reward: -284.1612948527324\n",
      "Episode 7, Total Reward: -209.63836560062035\n",
      "Episode 8, Total Reward: -119.62320637774707\n",
      "Episode 9, Total Reward: -198.68486056274736\n"
     ]
    }
   ],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True, render_mode=\"human\")\n",
    "\n",
    "deterministic = False\n",
    "\n",
    "for j in tqdm(range(10)):\n",
    "    state, _ = env.reset()\n",
    "    accumulated_rewards = 0\n",
    "\n",
    "    while True:\n",
    "        with torch.no_grad(): \n",
    "            next_state, reward, done, action, mu, sigma = interact(\n",
    "                state = torch.tensor(state.reshape(1, -1), dtype=torch.float32),\n",
    "                policy=policy,\n",
    "                deterministic=deterministic,\n",
    "                featurizer=featurizer\n",
    "            )\n",
    "\n",
    "        accumulated_rewards += reward\n",
    "        state = next_state\n",
    "\n",
    "        if done:\n",
    "            print(f\"Episode {j}, Total Reward: {accumulated_rewards}\")\n",
    "            break\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-2436617277fd8ac5",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## 2) Actor-Critic with TD(0) Targets\n",
    "\n",
    "Write an actor-critic (AC) algorithm to land the lander in the landing zone.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-2f6e82b9fd39ab28",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "Use the following cell to create two function approximators. One to estimate the state values (critic) and one to decide on the actions to take (actor). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-ee84b13c4cd3bb0b",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True, render_mode=\"rgb_array\")\n",
    "\n",
    "state = np.reshape(env.reset()[0], (1, -1))\n",
    "input_dim = len(featurizer.transform(state)[0])\n",
    "action_space_dim = len(env.action_space.sample())\n",
    "\n",
    "class CriticNetwork(nn.Module):\n",
    "    def __init__(self, input_dim):\n",
    "        super(CriticNetwork, self).__init__()\n",
    "        self.fc1 = nn.Linear(input_dim, 64)\n",
    "        self.fc2 = nn.Linear(64, 64)\n",
    "        self.fc3 = nn.Linear(64, 1)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = F.leaky_relu(self.fc1(x), 0.1)\n",
    "        x = F.leaky_relu(self.fc2(x), 0.1)\n",
    "        x = self.fc3(x)\n",
    "        return x\n",
    "\n",
    "critic = CriticNetwork(input_dim)\n",
    "\n",
    "for param in critic.parameters():\n",
    "    param.data.mul_(0.2)\n",
    "    \n",
    "actor = PolicyNetwork(input_dim, action_space_dim)\n",
    "\n",
    "for param in actor.parameters():\n",
    "    param.data.mul_(0.4)\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-6a0128a78a488e3b",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "Use the following template to write an AC algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def learn_critic(critic, critic_optimizer, state, next_state, done, gamma, featurizer):\n",
    "    \"\"\"Updates the critic network based on the provided states and rewards.\n",
    "\n",
    "    Args:\n",
    "        critic: The critic network to be updated\n",
    "        critic_optimizer: The optimizer for updating the critic network\n",
    "        state: The current state\n",
    "        next_state: The next state\n",
    "        done: Flag indicating whether the episode is finished\n",
    "        gamma: The discount factor for future rewards\n",
    "        featurizer: The featurizer for state preprocessing\n",
    "\n",
    "    Returns:\n",
    "        delta: The temporal difference error for the current state\n",
    "        critic_loss.item(): The value of the critic loss function\n",
    "    \"\"\"\n",
    "    feat_state = torch.tensor(featurizer.transform(np.reshape(state, (1, -1))), dtype=torch.float32)\n",
    "    next_feat_state = torch.tensor(featurizer.transform(np.reshape(next_state, (1, -1))), dtype=torch.float32)\n",
    "\n",
    "    this_value = critic(feat_state)\n",
    "    with torch.no_grad():\n",
    "        next_value = critic(next_feat_state)\n",
    "        delta = reward + (gamma * next_value * (1 - int(done))) - this_value\n",
    "\n",
    "    critic_loss = - delta * this_value\n",
    "    critic_optimizer.zero_grad()\n",
    "    critic_loss.backward()\n",
    "    critic_optimizer.step()\n",
    "\n",
    "    return delta, critic_loss.item()\n",
    "\n",
    "\n",
    "def learn_actor(actor_optimizer, action, mu, sigma, delta, gamma_k):\n",
    "    \"\"\"Updates the actor network based on the provided action, mean, and standard deviation.\n",
    "\n",
    "    Args:\n",
    "        actor_optimizer: The optimizer for updating the actor network\n",
    "        action: The action taken\n",
    "        mu: The mean of the action distribution\n",
    "        sigma: The standard deviation of the action distribution\n",
    "        delta: The temporal difference error for the current state\n",
    "        gamma_k: Importance sampling weight for updating the actor (gamma**k)\n",
    "\n",
    "    Returns:\n",
    "        actor_loss.item(): The value of the actor loss function\n",
    "    \"\"\"\n",
    "\n",
    "    actor_loss = - loglikelihood_gaussian(torch.tensor(action, dtype=torch.float32), mu, sigma) * gamma_k * delta\n",
    "\n",
    "    actor_optimizer.zero_grad()\n",
    "    actor_loss.backward()\n",
    "    actor_optimizer.step()\n",
    "\n",
    "    return actor_loss.item()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-fa43dbbddfe825eb",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e400823c7c014604b0e21ae2b380ba08",
       "version_major": 2,
       "version_minor": 0
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      "text/plain": [
       "  0%|          | 0/500 [00:00<?, ?it/s]"
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     "output_type": "display_data"
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    {
     "data": {
      "image/png": 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sDqsx4cDGEcMwDBP/FbJV48jdeJaNIyZ02DhiGIZh4r7OkeytlqWF1dg4YkKHjSOGYRgmYcJqXASSiQRsHCUBew5X4y8fLcHi7WWx3hWGYZiI0eh0oVL1EBkbz7LniAkH7q2WBHyzbA8mL9uN9BQHhnQqivXuMAzDRLTGkV5zpDWerW8U3dzD7c7OJCfsOUoitzMLFBmGScS5LSMtBZlpqR6eI5cLqG1wxnT/mPiFjaMkoKJWMYp4omAYJhE9RwWq10hfBJLg0BoTKmwcJQGyGFptA08UDMMkbnVsIjXFITxJBHvL448dpVVCI/v2r1tiuh9sHCXR1VVtPXuOGIZJvDR+KcaWuAtBcpXseGPJjkNCI/vl0t0x3Q82jpIA6VrmsBrDMIlEuSGNX6IVgqyL3pxHYu94nFIPV9fD6XTBrqzcdVj87d++IKb7wcZRMnmOOKzGMEwiVse28BxFs7/aXz9bib8vTMX+I7WIF9aWlGPoI9Nw9xcrYFdW7JTGUWFM94ONo6TSHMXhZQ7DMIyfCz+95siYzh8tftl0ANWNDqzeU4544eulu9HgdGHVHsUAsRsulwsrdyv71o+NIybaVMlsNdYcMQyTwNWxJdFuPkvVt0srlfeWf+OBmev2i791Nr1Q3nawSngDSVB/dOv8mO4LG0dJAIfVGIZJZEG2l3EUZc/RvnJ3KO1gZR3igb3lNZqXy65RhBWq3qh32wKkp8bWPGHjKAlgQTbDMImdym+lOWqMWkumeDOOZqleIzt7jlbaRIxNsHGU4FAMt1LVHNn1hGAYhgmFck2QnW6RrRYd46ikvCbujKOZ6/dpt+16obzcJmJsgo2jBEfpL6TcJiFeQ6M9TwqGYZhgqaitj0lYreSw2zgqjQPjqL7RiZ/XH9D+t+OFsstGYmyCjaMEp1IVY0vq2DhiGCbhw2ppUQ6rxZdxtHhbGY7UNiAtxWFb/ek2G4mxCTaOEpxKXddqgjPWGIZJvFR+8yKQlFUWbc/RwQr7G0czVL3RiO4txN/6RpftCkGusJEYm4j9HsSIl19+GV26dEFWVhaGDx+O+fPnIxGReiO7x5oZhmEi0VtNH1aLVhHIPQbNEYWE7MzMdYreaFzfNraNIqy0kRg7aY2jTz75BLfddhseeOABLF68GAMHDsS4ceOwb59bsJaoYTU7ulMZhmGChQwSWefIsrdalDzlJbpsNbrgjFb4LlJerrUlR+BwAGP6tLbthfIKzTiKvd6I8DyikoRnnnkGV199Na644grx/6uvvopvv/0Wb775Ju666y6PbWtra8WPpLxcqRNRX18vfiKJfL1Ivm55lfsKh6isrkN9fQaSnWiMNWMOj3XTkUxjXVvfKMJDRFaq52dWHUeorIn8PE1JLcaWISWHKtGpeQ7syPTVe8TfAe0LUZTl9odUVtciJ80+hu4K1Tjq1TrX6zuL1HEdzPNtMjRNR11dHRYtWoS7775buy8lJQWnnXYa5s6d67X9Y489hoceesjr/qlTpyInJzonw7Rp0yL2WksOkABPnSkA/DRrNjbkRezl455IjjXjGx7rpiMZxrpcSH3S4IALs6ZPhao1Fqzbr8x7O/bsxZQpUyL6vodqAacrDSkOFwrSgUN1DnwzbSa6xF5DbMon68ggSkFblOK7775DuiMV9S4HfvhxOppnwhbsr6YQaRrSHC5sWvQLtqZE57iuqqoKeNukM44OHDiAxsZGtG7tdi8S9P/atWu9ticjikJwes9Rx44dMXbsWBQURDY2SlYtffljxoxBerpnDD1UKhftAjas0v4fNnwEhnYuQrITjbFmzKGr6lmzZuHcCTzW0SaZjuutByuBRb8iNzMdv5s4zuOx9NX78N7GpcgtLMKECcMj+r5LdhwCFs9Hm4JspDVU41Ad0HPgMJzaqxXsmMJ/z+IZABpx9cSRGNChEH9f8hPqaxow8oST0K1lLuzAtytKgKXL0addIc743XFRO65l5CcQks44CpbMzEzxY4S+oGhNPpF87VrV7SxpRErCT5rBEM3vkQEanS6c+9oCVNem4pyJqTzWTUQyHNfVqta6ICvN67Pm5yjSgZp6Z8TH4UCl8sZtCrNQU06eCAcO1zTacrwXbj8odKctcjMwuHMLpKQ4kJmWiiNogNNhn7VgTUmF+Nu/QzOf+xTucR3Mc5NOkF1cXIzU1FTs3bvX4376v00bt5I/YVP5WZDNNHG25P6KOlTUO7BbJ2JlmEhlquUZ0vg9BdmNUatx1KYgE3nqWnvApun8sir2qKNbCsOIyExLsZ0ge4WqNyLPll1IOuMoIyMDQ4cOxfTp07X7nE6n+H/EiBFINCoNWRR2rIzKJC76ulq7DnkmBzBMNNL4PVP5G6OWqdamIAv56faudSSrYp/cs6V2nzSOYrUWVBou2EVl7F32qYydtMYRQRqiN954A++88w7WrFmD6667DpWVlVr2WmJ7jtg4amq+Xb4HN3+8JGp9nuyM3lO5+1Byeo52lFZFrRhhtKCqzz+u3mvr+j0yjd9YAJLIyVDuq4mGcVReq4XV8tKV8Smt9MxeswP03W05UCluD+jQTLufKlDHIoqw+1A1bvl4Cfo+8AMue3O+lvG3vbRK9MizS2XspNYcXXjhhdi/fz/uv/9+lJSUYNCgQfj++++9RNoJWeeIK2Q3Oa/M2oiVu8px1qB2OKVX4h1jvtAb47uT0HO0eX8FTnl6lqgv88YfhyEeoEX1z+8txIKtZXhh0mCcObAd7Fwd21jjSB9WqxK9JV1wUJGfiHuOMrFdeo5s2EKEQn0UVqSP3q5ZVsw8R5W1DXht1ia8/vNmoQEjZq3fj9Of/xnP/H4gylUjt3ebfFtUxk5q44i48cYbxU+iw5qj2FOhuv8PVyd+7RmfYTVdy4VkQWRUib5Ryt94YN6WUmEYEd8u321pHJHRQfqbtoVZETU+IhlWo4QAqoWUkeaIuOaodUEW8tLsqznaUValhf9IhC2Rt5siivDt8j14aPIq7FO9RMd2aY4rju+C537cgHV7j+CPb85H1+Jc24XUCPuYaUxU24fIuYvDak2P1D1IIymZSPawmrxSbjBkjdqZf83cpN2evf6AZUjwhekbMfLxn/DDqhLYLawmPUdEJMPZ1I9sb7lekG3fsBqFc4mORZ71+DKayHP0/co9uPGjxcIwogKZr146BJ/8+Tic3r8t/nfj8bj0uE5iOxn6s0tlbAkbR0myMBdmK1dXbBzF7juguHqyoT/eklGQLY3Demd8nHcrdh7G7PX7kZriQFFOugjLzNmkiHqNVaLf+22ruD1LFf3GrOmsSViNDADZgb6qPnLnHYXPyBNFF5st8zM9BNmR1GeRERbu6+0sUy5GOjTP9rjfna0WvSjCku1luPnjpaCPcNExHTHttlEY36+t5mHMSk/F/53dXxhMVIqBvqrh3ZSmuHaBjaMkCas1z83QSu4zTQdNcLL5pQwDJKtxRD2eKMzR1GzYe0S72m9q4s1zRPo44owBbfG7AUo4bdpqz7InxM8bD2ihJBpfK/YdqcFj363RvBiRRF5smHmOPNL5I+g5ksdRy7xMoY+RqfwNThfKZeGlMCHDc8ILP+PUp2eZGqaBIse8QxN7jrYfrMKf3lkozv3RPVvi/87u5xHW00MG06w7RuOHW0Zp4TW7wMZRkoTVmqtF0dhz1LTQeEt7oKI2GTVH7oWJFhBaLJs664oWmkv+PQ+xQIakZA8wO7NpfwW+W6mEyK47+SitSemPa/YJT4aeLxfv0m5v2Fdh6eV469eteG3WZrw9R/EyRRIZps4z0RxFK51fq3FUqAicyc6QgvADEQqt7SirFo1iNx+oxMVvzMO9X67QQoiheI46Fll5jiK/FhyuqscVb88XHra+7Qrw0sVDkOZHZF2Um4EeNspSk7BxlODIbDU6AAk2jpoW/VVrsnuOiF3qhN1U0PuRYUJZY7HwWsnP3xAHYTXKKCIb57TerdCzTT6Gd2suFn5KuV6285BHOGvqarfOiBINjI1YJbJ+TSiLezjZanrjKJJlFPQ1jiRUfVoa4pFAniPSw/PBvO0Y9+xszFynFHQMVpDd0dAQ153KH9ljsq7BiT+/vxCb9lcKkf6blx+DXIvvJh5g4yhJwmryBOZstaaFUoklySnINhhHTSzKlosy2UWxyBaUC7Pdw2p7DlfjyyW7NK8RQaGQk9TigfrQ2vcrS0S4sFtxrvgh1u9V2j8YWbPnSNQuyuTclptpHrLR0vmj4DmixV/SIk+ZWw9WRMZztOuQYtSM6NYCH149XIiZdx+uweVvLcA3y3cH9Bp0ISATIIzGUbSy1V6dtQm/bS4VxioZRpTNF8+wcZTAUOxangCa54jrHDUpVbpSCsnpOWo0dfU3FUd04x+pK/tE9By9MXuL8LAN79rcozH1WDW0pjeOvlKNqLMHt0eP1nni9noT3RGFUA+oBkM05h3pObLyTuRkRL6FCOnmiDaF7lBV85z0iKbzS89R+6JsjOxejO9vORG/G9BWS40PaD/La8T3mZ7q8PByRUtzVN/oxPu/bRO3Hz6rL3q3jWxT9ljAxlECo28donmOGu09SUcCumKyS0Vi/VWrLHaWTBgXxaZO59cbpLEwjuLBc1RWWYeP5m8Xt68frXiNJCf3bCWyvkhXtPVApTAOflVFwmcPao8erRStCD1u5TUiaqLgsa4MMKxW3WSeo8gcXzvVc6R9s2yt2veFx3QUt0mLFIwYu12zbJF5GO1stelr9oqU/eK8DE3IH++wcZTAyCwpunqQV1eJ7jn6YN42HP/ET7jmvUWwm3Ekr3STCek5SYErpmG12BlH0nMUfmp2tFi8vUx4VyhENqpHscdjVAKEtEfEj2v24utlu4QuaVjnInRqkaN5jswy1tbsKdduR2PekXpKK89RdnpaxMNqMltNHzKSmcCRqnUkPUcddELqXm0KtKKicl4PpcZRqJ6jNXvK8cD/VlomVLz/m2Jc/35YR+31453E+BSMn5h8WpPUtrCDoPTeL1eKydtXenFTUq2rsZLMYbXmWbERZOt1XrEJq3lm69kR6fEgY8es0vVpvZXQ2tTVe/GFmqV2zpD24q/shUVhNaPx52EcRXjeoYW9TvWC56l91Cw9RxHyIsuK4EbPkTSODkRKkG3wHBFUU4m8MjTEVvouY8Yb0dFQ4yhUzdGjU9bgnbnbcNfnK7y+Zyri+MvGA6L206RjlcKOiQAbRwmMdmWVkdakJeObGjpZn566Do99t9aybYpdPEd29R5EC3m8tcpye46acgz0mqOyqhgYRzqPiV1Da6XquMhyH0ZkSv/8LaUirJORmoKJ/RUNDNWmoagN1RwyZqx5GkeRnXf03hMrQXaOVucoMnMB1TGShpZM5ddLFiIhyCYhtdQ1keZIj/QerdWNqxU7LWochZKtVl5Tj7mbDorbP63d51X36sN5itZodM9WXuLveIaNowRGGggkTIxmbYtYQvVXHv5mNV78SSled/nILpreyg6GSJWu8S9NfJEUh8YDUnPTKtttLB6qqo9JWC1SmpBg0HtM7FolmzRHeg+IEVpg9QLb0b1aoplqSFGl4y4tvDPW6HunlG79/5FEhqhpXrOqoxNpz9GecsUbQ5XD6XNHI5WfwnbkYSSdV6t8TyF1rzb5AeuOrNL4PRvPBjYuM9ft9/B6PjR5tabjou/100U7xW3ZDiRRYOMoCQTZIqyWrhpHCbY4v/DTBlFoTmZJ3D72aM0QsYMhaNQHJFtoTX4H2akuERZoat2Rfrxj4TmSmiM7e45kR3mZ0erLe0ScM1gJqUnMMtY27PWsKxXpc1F6xa3E2NEoAukuAOnp0XF7jsI/vuS5QZ4po5C6l2qg6j1yVuwo9dYtheo5mqZ6iujCs11hltjHl2ds1LLn6GKHQoAnHd0KiQQbRwmMvg6IDKtFu9lgUzN1lXLi3juhN/44oosIIdpJAK2vc5SUxpFqHJBtThNrU6fz68dbGgFNid5j0hCnniNifN82mtdkdC/PRVDqjjbscxtHcgHX2hZFeN7xl8avr3MUKa/VXmkcFWR63K8Jsqvqwi40uttEb2TmOfLlFSdv5V5VOG0myHZ7jvx/J3UNTsxcqxSfPHNQO9x/Rh9x+/XZm0VhVUqAIS4e3snLmAuLxgag2l14NBawcZQErUNyheYoMcNq0mU+sGMz8TclxaHVN7GD7siYRhyNSsF2RoaVhHGkTvhN6zmq9zICmhL9+WZ7zZEP46hPuwK8fcUx+OBPx3n1yTqqlcxYc4fVVqvG0SD1vIy0x1qfbGJFThN5jshgJMheCdc7KS8cjHojOc5kgFAxU6pjZMXuQzViX8g4lN5aPcGsBfO2HBS6veK8TAzq0Azj+rbBSUe3FGL4695fjMXbD4lsaMpSiwiHdwEzHgOeHwD8+ABiCRtHCYzUu3iE1RIsW00aH/IqUdYFsY3nyMs4iv0+NSVyAqb5uH2zrCbPWNMfA7Gsc2Rr4ygAz5GseURGkhGzjDXpORosjaOIh9VkjSNzMTYhdUGRqnNUYpKpRpDmSRpI4R5j8sKhg4nniD6PrEi+VldDyrrhbLZp9mEwUYQf1ZAatZShC096vYfO7CtE+evUMCoZTJRNFzLORmD9VOCjScBz/YBZjwPlu4BNPymPxQg2jhKYCpOwWqLVOZKaHqkv0E+YUpdgJ82RHQy2pkQuinrPUVMWgox1EUi9UWAlyKZK9n98c75oMGps8BrK+1UFeYjJcSmyyFbzR7eW7ow1KgRIBpLmOerkNo4imSAhzyN5IdQUFbL3qN4afaaaVzp/mBlr+urYZmi6o5LykMTYnpoj3+Picrk0vZFec9alOBfXntRN+/+S4Z0RMiUrgNdOAj68AFg3BXA5gc4nAOf9B7hxIZBibfxGm/jtCscEvDDnJnBYTQpe9caRdLXLsKK9PEdJFlZTFybhOVIXlVgJsmmRJC+C/lixg+eIuq/PXr9fWxSvV3ubhcLF/5mP9XtS0feYIxjQSSne6K/tgxwjKSwOFrrwoow1+hwUWpOvSeGWvu0Kte1o7tFneUWzOna4YTVqkbK9tArXndwd6Wo2nGw6a/QcES3yMkV2XriibHeNI3PDhnRHk5f58xypNY4sDKxANUerdpeLnm7klT/+KM/ioFRJnUJqVCT0OLVIaNCaol+fBWY+ATjrgaxCYNAlwNDLgZY9YQfYOEpgKlTPCV1daSdEo3IFZ+ZujTfoilsWgpM1TTyMIxt4aTispnqOHE2vOSIvjNFTR/qa9hnmi0a0jSMyGszQL1JPT12PoZ2KMLxbi6Dfi8TAK3eVw+ly4OZPlmHyTSf6NB70Oizy/BRkK6GhUKCMNTKOKLQmPTXdW+YhPystOsaRlokbnbDa379aKY4dCg++MGmwMJC0vmomDVWltiecWkc0L/vzHPVuK0XZAXqOts0Btv5Kr66IoijcdqQW3R1tUNXQ3ef+TFO9Rif2KPb63uj/9/80HCGxfz3w1bXALrWLQc+JwBnPAXn2ynbjsFoyeI4yUz1KukfSe0ST4T9/WBeTvmF6d7lnWM0+xpGcmOU+JatxpNccURgnkBYI4VKhe49mUhPSxLWO9OeaVSaTvoYMbfOXj5aEFJ4pr66HfKktB6tw9xfe1YytxNhUtyicbCN9xprUG/VpWyDq9ciXjaTeMZBsNRlyCzaspjeqv1tZghs/XIzDVfUibGgVVmuRmxl26Lasql7bVzPvlL4QJHmpasv3AQc2aEaPvgBkJ8denLHmDuCt04EZ/wfM+Acw81Hx02bR03gj/WnU66r3mzHNJKQWFrSfC/4NvHaiYhhlFgLnvAZc9IHtDCOCPUdJ0z4kNSpXcFSZ+odVe0WZ+guPadoiYHIiISeY9IzpJ0zpOYsl0ghoVZCJiv0NSWgcyWw1l/BM5GemiewX0h0dpTYtNYOuwKkVzIXHdhSVd0NBjjWJR+lqn+qxSGOgKSDDxCNbzUJzJD1KtI/kaaEmrrd8vBTvXHlsUAaLzJRKdZBnOAWTl+3G8K7NcelxncMWY/tDZqxRIUhZ5JPE2+ShprmHztVg9I500UVG1pkD25l6uasCCKtlh+g50jfJpdAgzW8l5fO198vP8vawRaKFiPQakbjZan4mo6kgKw21NVVwvD4aqNgJFHYCep4O9BwPtBmIcw6+jkkZ3yJzdwPgSAX6nAlkKdovonHF5+hWV4IRjQtITm2+L4eqhW6MDr9T1fYxYVFdBnz9F2DNZOX/7qcAZ74EFHrWzLIT7DlKYPSNGekkd0ThCm6j2o2bSuvHMlNNP4G6Bdn2Cau1VqvdJp/myO050ocL/NU6mr52H75fVYJXZm4Ku68aGRyyc3pTpvMbPbT1FpojaRzlZaXhX5cMEccz9ap6Sa36Hqxx1CwDuH1MD3Gbqsev3HXYv3EUohjby3O094gmxpZVtUPJlL3hg8W4+eOlIkxohrzw8VnnSNMcBTcP6I2p1/84THjdl+04ZOk18hlW2zYX+OFeJUXdD7sOKeEwGX42g+Y5EmWfkToXGWQYEYe3A/NfA947B3iqGy53/Q+ZjgY0dB0NXPcrcMHbSthK/aka8EfxtD+6VEPFR5basM7NwzacsX0e8OqJimGUkg6MexS45HNbG0YEG0dJIchWjAdNlB2hjDUKAUjxX6TbAwTjOdKn8RO5qjvdVsaRWjguabPVVNu1fYC6IwoR6dOSQ0EaomR0yEyspiwEaTzPrATZ8n4KQfVonY9/nNNP/P/c9PVYtK0s4Pcrq1Q+b24acNXxnUX6NemZbvhwsWXYWxqLRbmh641kxhp5uSj0tO1glds4cjpxbMp6pKLRo1q4LyikSN4zwqqeTyB1jqRxFOj7GucVmi/Ja/nvPw7T5k4zvZEUZHuF1Q5uAj64AJj7EvDq8cCab3y+765DNZZp/Hp6t87DlanfK/+cfDcw6WNgyB+BXMXDusnZFjfiLqT98UugVW+v59cPvRr1rlQck7IWzh2q7scipHZaHx9e2x0LgJVfABt/BHYuVLREh7ar938O/PIc8L8blNDe4R1AUVfgqqnAiBuoIB3sDofVEhhjuiu5t2miiJTmiEIjUhAdiyw4aXgYs49ytLCanYwj6TmK/T6ZsWl/BVbsPIyzBpmHMUJFeguMniN/tY6kvoMWR3oNY+HBYJrOCs9RbtN7jvThGZ+p/Or9Uhd47pAOYnEivcv0NXsxtHNRQO8nQ4a56UrCxT8vGIiJL/wijJVnp63HA2f09X6OalA1VzUzoULfT+cWOdis9lOjiwHhcfjmNrze8B98nn4iahtODOi1FusMQmkkG5GZqL7qHMkkDZqjKHnDqgebEXmhJ0Nbo45uiTcvPwYPT16N84aaezukd0XLVquvAT69HKg7AqRmKGGlTy4BjvkTMPb/gHRvA8ifGFtyYuZ69EnZhlpHJjKPvQbIaa6E1ZxO/LJoCS7/fCd6tmuu6A1MSC9qj6+dI3Be6i9wzX0R6Pi2x+NkSP+2WWk0O6aPUhndAzJ+fnoY2DIbAdP/AmDiM0CWd50su2J/840Je2GWcXl3On9kvDxbD0avsWQg1JgUgNRPmJGqjBsOsiO4LJKm7xJvJ+75YgVu+WQplqjhg0ChsBdpWwKpc0QEmrEmvT6k4Qy1aKQ0RPMz07W+YXb0HNU1uD1HkgEdFI2IzJAKBGn4kedIiqzvGKekRS/faR5aK61UwkDNw/QcET1U3ZHmNSKvwsL/iP/PS/0ZOZtVb4cfFm3XGUcWHi9NkO2jzpH+oikYUXZ1ndNrXqFU9h9uHYVzBnfwGVbThPRT/w6ULAdyWgA3LgBG3qTcT4LkN04B9q21DKuZtQ7RM2zPx+LvZJykGEaSlBRsqGuOBqSZtg2RkBH+74aJylPWfK14e3SQgdvgdKFVfia6qkUnBXtXKYUa/3OaYhiR0dfxOKB1f0X3ROn4FDYr6AB0GgH0/z1w4u3ApE+Ac9+IK8OIYM9RMniOVGPBHfuPjJdn6wGdcRSDyttywpP1TLwF2bE1REiQK3uruT1H5pM9hU/e/HWLqBtCPcioRQH9pbYovkIHkUJO6sF4VrYfrMIT368VmWBnDGxn+vnrDMZR+wALQeo9bFRvpltL98IrIW/AUz+sw4juLUT1Zl9hNTt4jmh/fXmO9J6Ndmpmn2xZEWi2E6G3czq1yPFpZJWqzwm1AKRRd0TiZWJk0WHga8Ug2JnSHh2cu9D9t3uBY8cCuS2C8Bw1hFzniC4GyXlCBjbpiMyE1D7D9UHUw5LZauTxrF/xJdIXvKE8cM7rQFEXYOwjQPfRwJfXAvtWK+G2m5YAqWkmNY58GEdlW1G4fZq4+UrNGJx0pNajOrVW46i59WtQgsIaV2f80tgXJ6SuAua9Boz7h/vzqxeV+bIMQ+UBpZXHkg+UkgCOFGDQxcBJfwOaNW0STlPCxlGCIhZmL89RZKtkbzng1oMEG9ePBPLzGTM77JLKT2Mis2z9hdX+NWOjECEboSvw724OLBwRDtJgthIN+wrj0Gcyq52lN8KDDatJMTWxw2JbEi2/NnszZq3fb2oc6QXZ0nNUGkvPkVUqvzrmlDQhkdqWPWrhweA8R+73kSnhe8trhEbQmP0mnyMF6+FAeikiE3W4cMsjSkip00jcVXMH7iv5C3rW7gSm/BW44C3L1yBjepnOy2XlOdInm3iw7nsgLRPodrI4Him0RjWRgvEiS+PIX0ZvyqzHMWrdF0jJWojCHmORmdKIVq4DSJ18v7LB8bcAPU5zP4EytK79FfjXcEVEvWk6cPS44MJq89+AAy7MTx2ETa72WFdyxNM48lMdm6BxEd6jxomKcbToHeCkOxXPj/j8quFJQkHydE1/GKhRv5O+5wCj7wWKFcF/IsNhtQSFFiZZV0V6VhItrGbpObKJIFufJUMuauOir4faLhC/G9AWFwztgOOPUq6uKZ25KcZWGjLBdI6Xnhk6zqT2zOw19YJsKTYlLZFVUUTx2rXuRdFKlC0zJferY+e9f8pYF2Sle3ROj5nnyE8qv6zETLRVm5uS5yjQthsyW02G1YiWeZkiHZsMM7MChTLMGAnPkQyr3ZP2AQoPr1FCSuf9G8jIxe3118JJaeWrvgBWfWn5Gqt2H/YoimmlOdK3RtIgwfNHFwLvnQ28cjyw7GPkpbuCDqvJ8y1bujvNWP5fpP7yTxRVbUbq3BeQ8u7vsCjjz/hvxiNIIaOw43DglL97Py+vJTDgIuX24nc95grp+bM0jmqPaM+Z1/JC02KQ8lzxFVaTa8FM50DUFR2tGLG6famtrsGIlFV4tvw24NvbFcOoTX/gqmlK5lsSGEYEe44SFL1h4BZkRzGsFgPPkZbKb9OwmrxapXGncJmcpGkx1C+E+rDW1Sd2E6E0WhD73P+D2J5CItTPKJrIBSGY5qh6L1hNndNLNC1bh9DiLB0W1N2b3PpkTNHnsrrC9QirqdlPZiJyaRRQ4T5qjGkaVstMcxtHTRlWMyzI1qn8UnPkPiZaF2Zq5yotmoGkU2vGkS56RKG6VvlZwhglQ6uVIdtKeo6CTtcu3wOs/AzY/puieylojx65bXFXwWJcVjfNHVIqbI/MtN1Y6eqGNd3/hL4bXxMibXQ+3rTwnzE7z8xzROeGV7ZaXSXw3d+U2xT22bcK+PLP+NpRjNdTx6O6eiiZycEZR1ZhNcrKmnyLuLm9+fHo0K4dUjb/hLyqg8hzVKE+oxnSz38TSLUI4w35A/Dby8D674Eje4H81prXiLycZMybsvQjoLYcaHEUGskLtXUT1pYc8RgXWSLDV1hNzklH4MCBAVej3aw7gLkvAwfWA3uWYVzJKpye0QDQEFOhxlPvA4ZdGdM+Z7GAPUcJipbJlZ6qudKD6cbsD9JPkBZEEsnaSeG6v91htdgKsvWeLdK9SIzeI5rUZJZLsephItd3W1V3sjuI0Er4YbXgPUdWV+byNaX2gyADRuppfImy9caRDBUYoSrBBDlID5t4GPTZanLxP1RVZ1mpOmap/KpHSR9Wo3NVinwDDa1Jz0Oe4ZJX1uYx6pfouJOetICMI/JcLP0QePcs4Jneiuh47TeK12HmY0j79iZcW6dmPp1wqxZSklrHJV2vVsS71aVKQUAyaAwsVsXYskaSmeaIjisZotSMo1lPAuVqQcRbVwOnPiBS21u7DuC+9PfR49sLvITHgdRP86KuCvj0MqC+Es7Ox2NJp6vReNYrwF834L5Wz+PR+kn4ecS/gUJz4baA0us7HAs4G4BlH4m7dvrTG9ExMu9V5fbwa9GrbTMvzxEV35QXhB38eo6Uz3agy5lAbkvgyB7le9yzDCmuBhxy5eLX/NOBvywEjr066Qwjgo2jBMXM7ezuxhy+cbT7UI2HhiJSOqZQDEBjWE0K0GMfVnP3tiNPUZa6SBg9WiTilGEpffNPqRfZo9Y/iRZ64bSVLiaQpq5GpMFs9CgFojvSG156I1zPZtVzZJWFpmWrZaVrYSMrQyq2YTXVc2TwJkqjJtCMNTPNkVF3pIe0OPJ792scUSr684OAr64DNs9UhLmUqTTmYeDke4AhlwFHjQFa9VWylEa7Q0pZ6vdf3ZgKnPMKkJKmeE3o9UgM3FCrHYfSczS6Z0tLz5H+vM4lrzhlflEtIWLCk0BBW+DE24BbVuClvJtQ5spD/sHlwGujgA2qVytUzdH3f1ME1bkt0XjWa4qXikhJxaGigXi98QxsTvPds0xAdYkIMkj0PdXMjCMKqy56CyjdpHhyBk7SeqytL6nAv3/eLFLvZdsWXxW2JTKKUIMMpVJ17zOUzLLfv4sPR3yDQbWv47MOd9myrUdTwWG1hO+r5v6KI6k52qLTG8UqW82tDbDwHNWZC4WbCtniQBpvtEjX1Nd6TfgypEatNfSTmtSdWBXCixQeLS6C8BzJWkRWVYhlqFV6DiSBFILUG150m3pbFar90Qj6/4CuT5oMKVllq5FxSm0XaJ8ptBZ21d8AMIaarcJqcsz1niP5/VOFaOqM7g8KK5qF1Xx5jqQxRfOCqZfEWOW46oDShmLEjUD/84HmXf3ul1eFbNKuXPg+8P1dIvMK390JzHlRCIL3Z3VFj4qFGJpag3NSdmJtyj5srB7h9XrSIyy84jRkpIshL0zPCUq9H0l6Fn4pmICPDnTHN23eQNGhlUqW2Kg7gJPvsvSGWBWXxbJPVG2OQ0lNz/esAdQimHIRJGymMSCDZ9sc7D7UwlxvdKRE+XzkoSOOuQrIzEPHdJd4P3qv//t2jcdTOvqpk6S/UBbGMbUdoR+VfbvX09kdVLZeIsLGUYIiy+tLvRGRqZ7skfDySL2R7JUVC0G2XJCzDbVOpEFIXgJaoGJ1khs9WxTeIfGwMaxmDKlJKJU/kLT3cNEfD8Fkq+k/R42fsJoeWevIKlxEE7Z8Lnnb6Dsk71H/HCWbhth0wO018ii+p98/XViNIINIGkdNgfEixMrw1ATZhqrB0uNTEkBYjQxI6fTTC7J9vY4cB1pk/V5A7F6i/CUD5KQ7EAzSc6gZi2TAdD8VWPIeMPsppXry138B+SjelzbrHODNDGBJdU9gbzugdR+vApDiPF/+X2DbL0BaNnD6E17vTfPfLrTEj8e9gwsO/EupuzT7SaVmDzU8NfncWv00/bxB1a6/uVW5TZldlJZfX2/ZQoTCtz+sKsE3y/cIkfSDZ/b1zKjMzAP6nasYW4vfxa66az09R+QtopAbGVAkiCZv24l/BUb9VQtPf3TNcfh+ZYkQsZMRLS82BnfyXzTU14WypXGYZLBxlKC4GzO6D/BICrK3qMZRr7b5WLC1LEaCbO9ibfrKuHKBjJlxZBB2kiFpls4vPUf6kBrRVjMiou05ck+QoWSr6b8Ls9c1Gkdu/U+939ft2aZA9LUSxlEHt3EkKzH79hzJIpBu42jrwaomM46M54RVyNIdVnME5PHxWR07IxVpKZ7HF9XMMnsdOQ6yzEFAxlG7QQgW04U4LUPxglC9HEoXX/gmyiqqUVKThrz8ZmjVshj1W+ZisGMdXK+dCAcVUSSjJD1bC6u1yagGpt6rvB49ZlJzR84NS/ZUY+y4J1DY6TjgfzcC674VHht0OT4w44DCf/WVipCc6vv4aCHy3YoSfLF4l8f3fcXbC3DnuF649qRubkOUQpFkHK3+H8qKznN7jkjsTpqsjWoIsO1A4Kx/AW2UtjL6ulKyp530BJI+r2cb64bOpp4jC+MwJ8k9R6w5SlBIT+DlOYpgWE2m8fdqUxC7CtkWqfx0VUWLRKx1R7I6tvwOZBE6fZq63jiiTC6zxTHanqOaED1H/jVH0nPk+f3IzD0r7Y98XfoOu6hFDI2ibJmpJin1ozkimjpjzdtz5E+QbfCwSaMmAM2ZNA6LdKFHL8+RITyrNZ31ZxyRF2PPUnWnBiNYNI+12UUZtdEY+RdREPEP+W/g9LonsHzcp3Bd8jlOq30K3zceAweFzH55BvjXcaKIYrfvLsEPGXfi4+o/A5X7geKjlVCfCbIG0IfztmPo/03DHxZ0xoZ2ZygPzn89MM1RQx2w4lPl9gm3WYbjZP9E8qSTYUSicqpQ/vthHcQQUsHUmz5e6m5s234o0KoP0FCNfmWKIdS39Eflc5JhlJqpCMv/9JOXYWQGGblUWT2QVjtazTuT78SqflyywZ6jBMWd6qr3HPmYpEIMq8mrlJiG1UxOYnK5k4EYy3R+s7AaYQyrSe2MsRBfuybTHLm/u6Cy1XRGnqlxJDVHBs+RNI6sPUduo6aTmupvFGVLMTaNLY2zmcGjLwJJSFG2mZepaTxHzoCLQHoIsgP4/t0NZL0NHXdBSaVmkvRcyHHwaxxRJlPFXoDqFLX2v0gbCaThNc1Xa/YoaelDOjcTC3NpWktcW38rFp5Vi+LZf1c0SmVbQQ0zmtNL0rCRQPmMFxRPlAm3nnY0CrLT8cPKEqzbewQ/bziAvziG4fvMz+BaMxmO8t1AgWd1d+kF1YyDDT8oGXZ5bZRwmgWjerTEn0/qhpz0NEwc0BZHqXWfaMz7ty/EQ5NXi1Y7m/ZV4LU/DFXKWAz+A/DD3Tij7nv0TF+JrjPnKC/WdhBwzmtAq16IBr48R1b145INNo4SFC0u76E58j9JBQItoLKehsyaqIlB41lfZf5JlE2FFSttZBxJobheyOzLcyRT+cmIoKvNaIUHPQXZIXqOTATZVmE1v54j1egio0bWQTIWgpRp/EM6FYlK2UbjiIx1mQEoyyg01zQh3sYRhe6cLldAeo1AkXWe/Hnl5H4as9W0bMXD1X4TC2QafzN1bPXI6ux1hppJAReAlCG1lr2ADN8p4mYE4rGm8acSC6S5kYkIVO+Hzo197U5D8Q1jgCXvAw01mLc/HS8uqEDXLt3wyGWnA5nWYSQS8d825mjxQwY1NfN96gdgnrMXhqesBRa+BZyihuasikBSfSFi4IU+U9rp+7v79N5e99P39ocRXUQI7PoPFmP1nnKc/fKv+M/lx2DQgAvhmvYAemO7+HE5UuEgXRGJxq3qJEUAn5ojX6UMkggOqyUoXkXSIhhWo7RTchuTWLZT81xt4g20km+k8HUSy88tjcRYUGUVVvMSZNeaCrJpcZAGVTRrHem9flad4/0bR9ZhNXmVajSOrKofuz1H7gaaeuOIhM3b1LDusC6KMWM0juRrkD2Rp45/cwvPEZ0rF73+G857ZQ6+WW7dRDdYjB5ay95q0nNkKGIpjRryQFl52bw8RyaGDo2/NLz1IviAC0DuDj2kpg+r+dIlyhT+IZ3dxmlhtryYqFcMoOOuE/WTVrWciF+c/XEov4dPw8gI9ee7/uTu4ph4p2Gs+sZvaaUETC+6qK8YeY6IgRcjHIZ3a4HJfzkBfdoWCMP0otfnYurWehzoPEE8vt3RDg6qQj36nqgaRv7KuoTSWy4RYeMoQXH3Hop8WE2m8XdunutxAkWq8nag+DqJpbcmloUgtUKc0nMkw2pemiM1W80sJOKj1hEZo7d8vAR/emdBWIU9I+I5Mln4rLLVpHEktBkmBoNHWE3VHFEmjizeSL3WyAtDxnnfdoWmxpEMp5JhJCtnGz0mErqSp2OJXv6Wj5di+hqleWq4GEPNlr3VTBrPyrCOFOn7E2VLQTY1ATbDnbFWE7zmKAwxdqAXZYvU4o9DOynFDQkKh5kZ0dqFXwiLt+y3NtU5DA25bRTN0ur/eWwjDX0RViOtEWme2g2JSIiLMjX/e+0InNyzpTAW//z+ItxVdyWuqrsdD7Z9FehAlbyjj6/kHM5WU2DjKEGRE4i5INsZEb1Rl+IcZOkWvqbWHRmND7s1n5WTrMyeozo7vrLVjJ4jY2jFyN7yWny1dDd+XLMPH87bFplstUhWyFbvsxJkm4UY9a9LxiTpZUiLQ8aQ1N5IvVHX4jxNp+XtOXK/hkQaAdJjIlmhNjql9yED5roPFmPOxgMIF3meyWPRSs8lw21GQban7si355BSx60E2frX2ROscRSmGFuv3bGad6hG02LVczS0MymKFGQbDeMxUmFSwy0YcjLT0IA0lPa+xFSYLWu2CeNgKXWih5JVFyHoePj3H4dh0rGdxPBO31SB6c6hKG7uNgyjjU/NkY95NZlg4yhBkYaDnJj1mqO6MMNqbuMoV1ztpqlX5k2dzm9VBNIu/dU0zZG6L1aCbKmBMabye2QsmXgOZONV4vnpGyw7mAeVrRZghWx9LSJrzZF5EUg6ZuRxadr2Q2sYmyZa38jaL7LHmsxU69YyVxszL8+RQYztK1tt5a7DGOjYiIeGVGJMn9bis/3p3YVefb5CPT6l99aqbYm78ay3pkjqb6givS+0tPxgPEeaQeXDOCrfpXhXqM5O674IBX8XZfR9kgFE5zGVBgnYcxSicSQ9TnuOIg1ROrBzAbBrsZdxUFy5HihZAaRmAP2UVPtIQefAo+f0w53je2r3+Wv5EUl8RRFYkK3AxlGCIrU2+gM8cmE1ZZHq2iLX48qwqT1Hmmcmw4fmyAZhNbcg21tzRGMmDThTz1Eza8/Rxn3uppMktH1l5qYm8xzpvUaB9FYz4kuU7S7eqGyjibLVdH5Z46h7yzwtO4veX697kt4G+Rq+jKM9OzbhvxkPY9LKa/CvgVtwYo9i8d1d/tZ8rNM19gwWeT64PUdWFbJl41kz4yiwFiJSkG1l6Jh5jqQHzZglaRpSo35glHYfAlqrCov5YbnquaM6VnrvmfS0Go1+eU7ra7gFgywaeziluVKpmqBaSypyP9tt/Uq54+jxSnPdCEMhvutPPgovXzwEp/ZqhbMHtYcdPEecyq/AxlGCYnZ1pYnwwvTwSDGs7BSvTX5N2EKE9DZakUWTk1hOnPYQZHum8usne6qYLb8bWazQbHE08xxsUD1Hfdsptab+88sWny05rNAfD4FqjoyhwWCKQHqm81u3/ZDjIdP5pSjbbRzlim2kx0V6QvSvofecNjcxpOg7OvnQl8h0NMDhciL9f9fi38P345guReIzPjuNWimEGVZTDTTr3mrmmiMi0ObD7lR+P54jNTxHXqxDqmHq03MkxdiUWh4i/i7K5H5IAbq358gQVouQ50icn8deo9y54jOg8qB2fFDgrXiLqkUapIbfogSl/VPmmtTXNQW+dGDuIpBpSGbYOEp4QXZks9X0afxdVeNI0xQ0YViNJlqZHGcWG7dTWE0ab1pYTbdPUhxMYmyzVG2tv5qPsNqVx3fF8K7NxVXg0z+sC3o/9YtWoGE1o3Fk2j6k3jxbzZ/nyO31SfPwHMlaRzKsRp4jGjOtfpHOI2RsHSINJaMhtW77bkxKne42AJwNyPzyCjw1WFkoZ67fZ5qJF5znKNVPEUjl/gwz4yhIz1GzbAvPUYFneJaMUnn+WIm4PcXYoemNCNlw2WrekSFZo8DarTmqN73o0Bu+wSDnC3F+dhimfO+NtcBb44GZj6Nd3VaMSlmOtOoDSsf6o05FomGVrebvojOZYOMo4escRbZ9CF2901UnnTit1DCQ1JQ0ZVhNv2CZuX9tJcjWUvm9BdkHVM+RWUiNaOfDcyCNhB6t83DvRKW+ypdLdwkNTTDov7eAw2q1gYTVzAXZ/tL55fhIj4vec0SLujQopXFuloVmrI5NkCFlFGXXLXgPBY4qlKR1ACiNmrqTN9ah87SrMbFgs9Bjzd6wP6Ax8f78yljmZvgTZEvPkcPSqPFlHNGCplXI9uc5UgtByu3pezATgqsvHBHjSPMcWVw8yWr+xoucApnKbzhGZN/I3BA9G/J54n3pguS0B4C0LODAemDmY/gSt+Pl9BeUjQdcGPW0+lggvxNjWI1Cv1Ibl83GEZM8nqPwNUeybUjnFjmapyNLNpZswlR+uRiTJ8BscpcGSUyLQNarYTXVcyAXavJqyJpQByvN+6oZ+2LRYq/3ONHiLksAkAeF2gacObCdWM8enbImqJpTHp6jEMNq8mo+kArZ/qpka2E11Zh0V8mu1oo/0mIvj22zLDTja0ikl0kYUs5GHLX5PfH/yk6XKlWWz3sTOGoMHA3VeKbhUYxJWYgfVuxBJDRH1r3VrMNqeuPY6jslT5tc0IpMikDqNUfkLaHtZRKAz0w1aghLlaFJtByiGDuQiycr7aCV5yhcQbY8H2X/SXQ/Bbh9LXD2K3D2GIdaVxqyHeqxNHASEhG356jR8iInmwXZTCLirgViUiE7jLDalgNVHlfterd5U3qOjCErIzJDKJaCbOOkLxdJWsjkJKTVODJUx5bQc+QCv0enJ9qoeo3a6YwE6uNEoZk5mw5i5vr9UW0866U5CqLOkT6UYyrINobV1CweKnmwevdhLVPNl9BaC6sZFlApPhaG1JrJaFG/B6WuPDgGqYsgGUgXvgd0ORGZziq8kfEM/rD2z6jf/AtCzQKU5QQs6xxZFIE0FoK0qigudVt0nMmCi0bIuyoz2ch75KsXm4b0GrXuA6SZH5+B4M9jbSyWatQcHTZojuTcFmpYTZ6Pcg4RZBeJdP2q8z/EsNpXcVPdjai78JOAeprFI/I7MXqO5JyVmkIXndYV2ZMBNo4SEP3iK6+SAu1xFKwYO1bZaloav8XVjRZWi6EgWxpm1GtJ/M1IFZOO3rjY7yesZpXOL/VGR+m6cpM2Z9KxHcXt71eUhNh4NrhsNbm4ShFnoIJs98LnK5U/XWsBITOXZq5TjL5uxUrfKivjSOqWCjJcwPf3ADOfEA1E9Z4j55yXxO33G09Dn86t3TtAWVkXfwLnyFtQgwwMxjqkvzsReP98oGRlQONjVufIKmQpdV5mHlA6t5r7KQTpTuP3XcxRGlqU+VhaqYx781wfRk8EQmrGOkdm3q9KS8+RVVjNu29kMOSqRpiZt5OMgyPIwdfOkUjvNQ6JipXBqq0b6ak+29UkA2wcJSB612hehMNqW9QaRzKNP1aCbHctDvOrx1gLsqmwnbGCN0028vuQxoXUyViF1azS+TXjqKXbSNAbrcEYhZ6NZ4MLq7XKz4p4Kr9ZSExm8pBXTGaqeRlHHtlqyv71Lp0O/PYyMPNR4O2J6Jp+SNyfVbIQKbsWiBDKt5kTteasGhm5SBn7EJ7t81+833AqGpGqdEr/96nAvjUBjZEsgimPRStBdn2DtebIXyFQfWjSSm9kfB3yHJWq4dzmvp4TZtsQif77l33kAgqrZXuH1ci4Ct9zpNMcWVx0kTc8kY0DK8+RNBizkjykRrBxlIDIyYOcFPqJKRLZaltNPEexSOX3V4sj1oJs/VjoJ323cdTgIchu6cNzZFYIUKbxy87fkuwQvHieqfzBeY5aFWR6hygMr2sW6pFhNZnGrfd6ykVLv/jJ0Jo0wqhPlpdxpGsoWyH2z4Vem992v/jO+bhu/ZUYmbISA3a8L+76X+PxaNO+i+VCOHJQP/y94Sqcl/o8XB1HiMan+O5ORawcbIVsi5ClDGVaCaPdxlF4niOpX6PXkZ4jWSfKpxg7jDR+oyDfrFCsXJBl/SGJ9BzSBQ5dbMjny+ikLK4aLPJ8NMtCTJbWGVbZar4K6yYbbBwlIHrBon7Sd2uOQmsSS1cZ1HSW6KKryRETz5GPApCBFIEkI++wd4mdiKE3FvQTjTFjzS3I9hVW8/YcbLIyjuTEH4RxpBfSW+lijEiPnDTqTFP5A6hz5BUy0WmZ9JlmUpQt6a773FaeoxNSVqLg8FogPRe4egbQpj9y6svwXvpj6Ht4ltjuP42no397pT+bGSO6tRDf2dLK5lhx7BNKVtOW2cBqtUCgBWTkSS+JP8+RryKQHi1ELIwjt34oI2DPkXyOpceybCtQc0ipDt2qD8KBtCtyGvLVBT7XIluNpirqw2f0BMu2PMEipQZmF07J0pHeKltN1ivLYc8RG0cJnalmuBKTJwRNNoEugnqozgw9jSYxvacjEEG2WXw/HKrVTDC/guw6d2aY5HBVPc54eS5eWBW9CUA/ycrGp8arYQ9Bdr71wmasbkyTuiz22MNgHElDNZjaPDL8E0xYrdwkrGYc51DCajKEQs/R10eStY7k8dZWFwZrnuOtOSLj6JrUb5R/hvwBaD9EpOpv73wuUh0upMCFRWmDsc7VCf18GEe0D6f1VvRIX29LF13hBT/cC9QpXlQz9EaA395q0nNkMk6BtBCRho6/BrLacVReo4VzLQ0q2U+tdT9FpB4GdIEmM1rNLqCsUvlpvpJzizSi9U1n9edVMOSq86LZBYQWVktw48AqW00Lq6Un9ucPBDaOErnGkUGwqF+kQtEdrd97RAtpeHiktFR+8wX5s0U70e+BH/D2r1sQKeQVjpUgO1edAGm9NoZ8yGtE7vkDNdTQ1Nlk7Vv0mUsUlqIQllzYrLLVZCdvvXEkK0TTVb8xLCKNRbPsMSv0x0LgYTVpHGVqnhKjYRWIcWRM5Te2DjEzjkiMrV8Yi0xS+dvVbsKo1BVwOVKA465T7kzPxs5RT+GO+mswP2UQ/l6tZKj1a69UGLdiXN824u8Pq0vgGnkT0KyT0nPs56ctn6M3Avym8jfIbDXfYTWr5rMyROazmKOH56haGythUNFJsugdYMZjwIxHgZ/+ASz4j/KkduGF1My81v7qgflK5w+3OrZ+zjD1HCVJWMkyW437qsWfcfSPf/wDI0eORE5ODpo1M+9evH37dkycOFFs06pVK9xxxx1oaPA8AWbOnIkhQ4YgMzMTRx11FN5+W6dJSBCs6oDoK/DqvQXyiumpH9ZiyXbrZpuyuKDxStudrWa+sC7eXiY8To9+t9ajH1g4aDoFi0mMTm5pvxnFyTJDjLBKjw5//8yvhvVhNQoD0bpE67yvkIimOTmk1LrZoI6hPrQkke8XjObIowhkwBWyPTVHZlfi8hgzKwIpKznTc/QTtL7prB59WE2fxq8PDZGhSdoUMtQucX4t7qs7+gygqIu2LRkDnzaejN9X3Yk1jR1Etp1sbGvFSUe3FB6MHaXVWH2gHhj/uPLAnBeBg+b97OSFAoWUpGFg1XhWao6sBNlmfdHMUvn9eY702iXpZRPPWTMZmHwTMOtxYNYTwOwnga0/K09qPwyRwFd/NWObHV8tRMIVYxO5WraatecoWTVHyRJWTCjjqK6uDhdccAGuu069CjTQ2NgoDCPabs6cOXjnnXeE4XP//fdr22zZskVsM3r0aCxduhS33HIL/vSnP+GHH35AImGVGktX29JAMp4UM9buw8szNuHByastX3fl7nLTK21/YTVZbI0Wwb9+utxykQgGf5MYebZytUKQnvu1T2cclalX3U2lidIbRweOuBcomeLvK6xC3yuFs7RMNTPjKJSwmkcRyOA8R/p9N76nL88RjYM0XvUGqlXxRiqGKLfXi7GJZqphSYcVvVbl/u04M2WOuM9x/E0e2xoNCDL0/WUlkcFJBhLxw8oSoOcE4KjTRCVtfPc3U3G2uwBmqqYlsq6QLVP5Hb5LORxSqluHK8im725veY17PJZ9rGzQaQRwzJ+AY65Wfk6+B+h/PiKBr0xZq/nKrPmsNGgi4TkyM46MGaZJpzlKks+fUMbRQw89hFtvvRX9+/c3fXzq1KlYvXo13n//fQwaNAinn346HnnkEbz88svCYCJeffVVdO3aFU8//TR69+6NG2+8Eeeffz6effZZJBJVPq6urOpbUIE9gorsmRk5NCmvkp6jdp6eIy2s5qc9ALF0xyH8++fNiJZnxrwQpLXnqKw6OqrsKotQQV5muts4qvAvxpafUYZMSJQtjSOj3shDcxRMtppHWC04zxGFPdyhPHPjKEM1no2GuizQeFj3Hbhbh3jr5aTOSJ/GrzXtVbcnLY1j/qtIdzRinqs3Mjp5ej6MBoQvvZGe8f2U0Nr3q0qUlhPjn1AqR1N6/7rvLD1HdOEgs9CsBdm+s9Wk54jG19iE1SOV349xJAqKGkJ8zVMqgA1TlQ1+9xww8Wlg4j+Vn5P/FlbxRz1WmbJCuK4eJ6ZhNYNwP9waR/rnmtc5ciaF5sbSc5QknrNASJi2u3PnzhWGU+vW7mJu48aNE56mVatWYfDgwWKb0047zeN5tA15kKyora0VP5LycsV7Ul9fL34iiXy9cF+3XF1sstJSvF5LnBS1QGV1Lerr3ZNpqbpQ01Xs8u2lGNzJM3RJrnhaeMhL0L1FlsfrpqeoabZ1Dab7Xqn24RrZrTnmbC7F09PW46QeLbwWuWCQr5mZ6rAcL5n9cqiyBvX17rDM3nKlyjdx8Ag9Fnnv0ZFqZTyz0z2/g9x0xTtwuLoW+w4r+9EiN93vPlAdHloEdx6s0EKTXZpnez0v3eHUJrlAPxd9bxLybgTyPJlVRjYJfUY6fI5UeR5TciFMdSn7ZHxd0h2JVhZHatC5KEv7ruR3Z9z+nMHt8O2KEgzvXOj1GIXHRKjywF50Xa60BPkw9SwMMfks5I2QgvLerXMD+ryjujcXHqD1eyuw/cARtC3sjJTh1yF17gtwzXwMDd3HeI6Peg4Ko8DZ6HNstdo/TvPvLFX9fNRcdvvBI+iV7i78SciaRfmZ7nPB6jO1LsjEkf0Nmqcqe+1XgLMertb90VDUnZ6IaCCNo6qaOo9901dap2PXuN956jlcVknHVj3Kq2q1TLVQz9sMdb6iiybja1TU1PmdVyI9X8eCVFejduyR80B6TytUIzQzzf/nb0oiNdbBPD9hjKOSkhIPw4iQ/9NjvrYhg6e6uhrZ2d7ag8cee0x4rcw8VaRtigbTpk0L6/lLd9KBnorSvbsxZcpOj8ec9TTZOPDT7J+xSed4WLKVJi9lAvtw6lzsaed5lbuiVHnN1llOTJ/mGYbcsFd5bNsu7/cjdu9V3rN3+n6UNXNgzSHg2jd/wc39GoXehiivAw7WAh1yydjy/xnXb1L2d8fWjZgyZYPpNvXVyvvOmjMPB9e4P8+KDe7POmfhMrh2qJk5EWSeOiZHyg5gypQp2v3bSpT7N27diYaDO8Tt2nLPbcxIrVX2+bufF2LrAbrtwPYV8zBlved2FeLcTxNX4998O0UbX18cOqKME1FdU+t3X8jpUFmnTB3zfp7pcUxtyXdvU9+obDP3l9mgWoNex3Wd8rzpP89FSZHy/SzcpYzP4f0lXvtxNP0cDcybPd1rn1LU1zo09Z9IrT+Cjc52mIO+pp8lA+7Pu3/9YkzZjoDISU1FudOBb6b+hPa5QEZDT4x1pCG1ZDnmfPYSDuV007bdKK6h0lBfU41ffyH9Tprl2DY0qsfpzBkotHD+5CAVZXBg8vRfsFkdK4KibAcrlecv+e0XbM30PYek1bmP/ewUJ8p/eR3NKWSe1h+b/Xzv4VCpHmNz5i1E5Ub3/ivlNNLggAvTp/6ghU4lZfuU/V28Yg1aH1qFBbvV4+PgXr/HqRVH1HOEkhaM58gyde48YDJ3Rmu+jgWKA1I5P7/+9jttzl2trgN7dmzDlCmRS6CJFOGOdVWV+8LY1sbRXXfdhSeeeMLnNmvWrEGvXr0QK+6++27cdttt2v9kSHXs2BFjx45FQYHvLJdQrFr68seMGYP09MA6QZO7+ce1+3B63zZaiGnFD+uBHVvR66iumHB6T4/tn1v/C8oOVmHYsSNwTJci7f7ZX64E9uwWt+vy22HChIEez9v400Zg3WYc17M9Jkzw7DdUv3Q3Ptm8EoXNW2LChKFe+/jypjlARQVOHHEsLivOxYQX52BrRQNmVXcU7n0Kte1U05SvO6krbjuth9/P/eOny4F9JRjYtzcmHO8W3Or5qGQBdmwpQ+/+gzBhQFvt/rd2zgPKlBBh2y49MGH0UYg0e+dsAzavQ+cONJYDPMbqsy0rkVtUjFZtC4BtW9G/RxdMmOD7GJ/XuBqr5u/EkZy2cGKfCA1MOnuMl16GdD/3LlSMh9GnjQ1Im/Hw8pkk6hO3HalpmDDBd9sEoRH6bYa4ffbE8Xhn+284uK8Cg4YNx/HdW2j7gd+U/Rh72in4ddZPXsf1J/sWYsemUhzddyAmDGon7ls9dQOwfQt6H+V/TPR8VboYW9cdwFCnUrjwzcbT0bq4CBMmHOe17ds75+HAjsMozE7DH87xHkMrnlr7M8rLqjFs+EjNs+pw/gSs+hwnZm1A44QbtW1/3nAAWLUYLZoV4NTRA/HYsl9Mx5bCSq65yoQ/bsxplqJq+ny71h1Ax6P7Y8IxHTw8L87ffhK3z504DmkOp8855OfaVVi7eJe4PaSwAs0rNoqMvl7n3YNe+UroMBp8snchthwpRd8BgzBhYFvPorKLfhUFHSdO9D7u1kzbgF/3bkHrjsrxsGnGJmDbJvTo2gkTJoRWf4mOzb9bnCNrf9wA7NiCHt38H3+hzNd2gcJpdy34Udw+5bQxWnbo3K9XA3t2om/PHphwSnfYhUiNtYz82N44uv3223H55Zf73KZbN/fVmC/atGmD+fPne9y3d+9e7TH5V96n34aMHDOvEUFZbfRjhL6gaJ0Qwbz2uzO34PnpGzBvyyE8c+Egj6J++dkZXq8jqxU3wuHx2JEatxZg2c5yr+et3qPoXKj7u/Gx3KwMzUVrtt9Vahy7ICcTnYrzcd/veuNvn6/AV8u8u52v21sZ0GevVdOf80w+oyRP3S/y3Ou32a8KoYny2saofI91qr6ENEb612+Wq4SPKuucKK1S0+ELs/3uQ/siJQQ5d3Op+HtUq3xkZHgvpKmp7lO6ASkBjqVekO3y+5xq5dJbhEpyszORrVWAdh9TlfUur+PDeFwX5Sjn1ZE693FTqR4rhTmZQX0vxXlZKEI5mpevFf9PaxyCo7LMz6MWatkE0huZjaEVUjDc4NKdO8f+SRhHKau/RMrpjwFZhdo2sl5Olqozox5qxv1p1Om0crKsj+V2zRQv9b6KOo9tKsrrNY1IQa473G01h7RTK40Tv3MozXQd3U5GenOlJ1+0yFL1RI36saPzxOnQ9EZm+9tM1eNV1CrHSI163hf4OO/9kZamJAOQ163O5UAz/f6oX0eu4bz1RTTXgmiRluY+P6k1jtz/Om1eTbflZwp3rIN5bkyNo5YtW4qfSDBixAiR7r9v3z6Rxk+QpUmGT58+fbRtjK5Y2obuj1dkI9gvl+7CNSd1Q682Be4ikCaiRWkcGYux6ds4UIHBfUdqtAJ/xEq1G7qZgNVfKr+7Aq5yuP1+WEchKqafQR2LMKRzM5Fxc/PHSz3E0r4IRDhoJrwkYfl+VV9l/NxREWRnWtc5koLsYj+CbH0attRoGHuq6YXOJAKm7yLQjDWP3moWLS70yH2QV5s5JoJsaXCRTifNQmhMDWW9s9Xkawc3NZHHZUTKahGeOZTXHftrijDY4jVkAdNAxdgSU+E5ZXgV9wQOrAOW/xc49mqPCxQqfiiF1mZZmvoMNitBtlmtK+/q2IFN+vI4otYqo2oUjxMGXIRoIzNajYJsf5XuZZ2jwwZBdjh1eMhTSMcsJYoYzxH53cr9TVRoDEh/SuF3fb87FmS7iZsjgGoYUfo9/aW0fbpNPxUVikeDwlxkBP3hD3/AsmXLRHr+3//+d9xwww2a5+faa6/F5s2bceedd2Lt2rX417/+hf/+978iCy5ekZVu6Sronz+s88jOMsv+sMpWM7ZxWLpdadBJkKG0t7xWXG31plCQ8TX9pPIbCyLSiXnvxD546+I+uLnHfpy4/xOctPwufJVxH7ofnhvQ5w6kHodZ81nK9tGnr0Yrlb8qgFR+2TrEV3VsYzq/xCyNP5T+asbijXQc+Su14M5US/OsraRbaOR7m6Xx+6qSHY5xRO1CiO3NhquvYW4wXHF8V0w6tiMuH2kejrXCNBOQTophVyi3F72tpfXLz9/NtR3Fb43EX9M+UUJohlR8fQabVfsQQjbGNbYQkS1TLHukGV9HNY4GOzaiVf0uID0H6DUR0cYqld+dxm/+fcsWIjKVPxJ1jsT7WbQXksdwMhgHmbKsi+549tezMpmIG0E21Sui2kUSyj4jZsyYgZNPPhmpqan45ptvRHYaeYJyc3Nx2WWX4eGHH9aeQ2n83377rTCGnn/+eXTo0AH//ve/RcZavHJQ12zzxzX7sHBrqXaA+0rlr2v0nBTkAtW3XQFW7S7Hkh2HMFatDEz/E92Kc001LL4qZNOCcFLjPNyX+R7avd6gLCYkhqW/1WWAmslECo5BKcCVdR/C6fyr39YAgaTymzWf3V/hubhEz3NkbqBq7UNqGpCqal18VcfW1/kJ1DhSJrb6gNL55ZV8ISrQxVGCZa6jhDcjNcV6XKWxKb1gZh4VrcaRj0lWM450VbJlFpyVYWMFGQfHpawQtzfkDfVpYB3dOh+PnevWgQWKZWuWgRcBPz4I7F0J7FwIdDxGfP4CVOLmAw8itX4XLk0twT8bfi8M0Yw0h6mnzmetK/X7363rr6cvAOkvjV97HdU4OjtVCamh9xlApvWxFCmsikBW+ygA6VEh29g+JEzjiLIh95uk8ydTnR+6qCVHvZnnKMfCWE0m4mYEqKCjv2rWnTt39pvBQIbUkiVqt+kEQBaAG9ChEMt3HsYT36/VPAFmE452BWcMq6kLFBW7E8aRrlK2rG9k1aBTc5mbhNVqdq/Cs+n/Qo6jFjAr8FvQHmg3GA2t+sEx6wkMSNmMQ7vXoVkH32LIQCrZ5qoneIXu6nBfea3p4hJpNOPNsH/SYBOp9uqkJDUwvmit6yVmVeMolEKQ9J2lowGfZjyEo1N24Yza//NbJdvo3ZFGg76onrsIYnCeI+khCNZz1N5Vgk4p+9GAVKzNoFpoB4J+DX9oHjljIcPsIqDvOcCyj4CFbyrGUV09nkt/WfHOkPHvqERXR4mohp2hc9hLzxEVZ/UlDJeeQ/IckfdJbitbhwTqOWpbkC2+7zNSVQ/tgN+jKbDyWFt5WI11juQxF4n2IUS2RZVsrbdaEnhOtILAunlb88hnxE1QKWrwCMQxNEnK0MwDZ/QVE9CCrWVYpeqDAi0CSWEmecVwck9Fr0WGlgyvrNwlK2NbGUcWYZy6SmR+eaUwjH519oXrhvkA/Vw/D7j+N+D29cBtq4GLPkDaKXdjvkMp8Fm//Au/n93yCqd0C/DycOCLa5Cf7jTxHCnj1Zxyy4Vmo2krZOuLG0ojxLIzumGM5XakFdD3GjPbVuxDQJ4jJ/6Y+oMwjIhjUtb57a+mVbFWhcbyM3p6jvyH1Zr5DKsF5znqUKYkY6xyHI2D9YqxGXHjyCR8qDFUDa2t+kJ4RAdufAWnpC5FvSMDrsJO4qFBjo1e/eekgWzVOkTv8aG6RLSYU60lieyRFqjmiMJUp6WvRHNHBWoyi4GuJ6MpkMdk0MaRrJCteY6kVzw840XWQLP0HCWBcSS9uuaaozQkO2wcxTFHqIiZOtlSOExqKDTPkU/jyD3By8WJLkYpRZmMKmUSPuIhxu5rqIztZRwZr6in3Im0g+uwz9UM9zhuhqNlT4B+WvUCWvUG8j1rTs3NHqXs9/qv/H52d1hNdwhTsb0vrwX2rwWWf4Ixq+9BKho9jSNV8H206nmhz079uKInyPb8Dkh0q594qWJxoFepMrRC4U3LEEx9DY53LUIBKgLSHNUf3oNb0tzGaE/HDq8F3IgsoCiND7N+bu7WIQGE1UzahwSrKSnep3hCZjf20/ZPViOPFNJDamp0djwWaNUXaKgBvrwOx2z/t7j76053aZqegSmbvAxPOda+9EbKe1MLE+XC5etliiHrKcgOzHNEHqeLMn9VntvtTECX3RhNtHnHMHZW4WfjMUJzHV2saWG1MMM+8rw0eo5kw+akMI7SfHmOUpHssHEUx0i9ES0kNHled3J3j6tleXVk2h1bd0LI9g20UNPiPbCjYgRR/SEKO+0sU3QOfdqZ13WiStzSA6UZGks/BJa+L2qo3Fx/A6ozlPo3vljT7CTUuVKRe2gdsE9JybbCrQ3QTZJzXwJ2/Aak5wKpGei490c8nf4KKmtqvfqqybAU7a4M5UQSWb5AZnJZeY+K1cypQJChFbOGs4Jtc4HXTsS9hx7AL5m3oOOqV4X3zhcFvz6GfEc1qqHsR6+U7VojVCuM3h0zLY7mOfKR9SNDJlL3RZ5QGTYxNp71ibMR2TsVDc2M+r5aFmCkPUeWHlKjMHu90k7kzYbxWN96AhwdlBYmg1I2eond5Vj7ylSTnKnWgpq8bI8m7C4LsOmsRsV+nOhUvGytTrgMTe2lMGa0+tMO6j2IpEeTyR3hhtXkealvbST2L4mMgwwT/anbI5+KZIeNozjmoBYiytAacF57krtwly/xtN69La/cZQPPQR2VAnekO5Ji7M4tcrSrOA9qypG7dRqGOdaig2MfamuqFcPm29vFw7sG3oy5zr4BTWY5hS3xs3OAOzxhgb4fk3aFt3c18NP/KbfHPwb8/l04HWk4O3UOrix7HlAXIek5Ii9MZqpcYFTjqCbwAmGB9rczm2T0i3ZxXuB1dqRBN8AY3qT9/uY24K3xwIH1QndT4KhC3zXPAS8MBhb8mwrqeL/gzkUoXPeJuPlU2jXi79GOnWio9+45pcfYHDbbh+aIUtmtkP3i5PFHz5e2Q1BhtZLlSKkpQ4UrG8td3bC9tMq0P1u4WPWQ0yD9DmV/UZPrvMF4tOFi5epcNY76OLahvs5TUC01R4EYR6f1biX2gT4fXbjosy3lWPplyXtIcdYD7Ycitb1SF60psOqt5i7zkWq5gMtxp4sYd1gtXM+Reswa+i66U/mT3HOUnvif3x9sHMUxMo2/hW6BveL4LiLs0q4wyzQLyldYTRo/gzsqlbOXbD+ElRbNZjWm/h1Zn12CzzIfFt6K7CfbCu8F6quAridhY88/B3wl0jIvE5Mb1ZpTK78w7XZuXJzESdxQB3z5Z6VLeo9xwJA/Aj1Px6YTnxNF58bWTgW+u1O8HpUlIFrlZSJXnV/LKiqBr/8CPN4ReO8cYNcihIuvK2LZ/DOQprN6rh99FF69dAgu06egb/hR0Vgt/I/y/+A/4N6jvsDNddfjSHZ7oGKvYqi+dIxSh0ft8yWMRRoTAJ83nojZmaNRjQxkO+qAMt+NgaV3x20ceWciubPV/AuyydCl50qPFIWYgqozs3mm+LM4pS8akKYlKQTlfQoAvyUSqADkuH+IDLB3Ozwo9kV4TJp1RqkrHxmORqTsVTLqJHUBao5k6GlMHyUU/fWy3cF7jui7X/SWcnvYVWhKtPpqXqn8Dd4eYIt0fpqnIuY50jRH5nWOksE4cHuOlO+EvP7JZBz6g42jBAir6QW9NIF+e9OJmHHHydrB70+QLTPV5GI1SG2NsHF/BeZuPihu921v0Splm6Jf2OtqhlqXevVKRkp+W+C8f0MtAh2YcZSfiR+dQ4SIFQc3ACWeC4lEL6IUi+jsp4T3QGQNnfmCWi4AqO15Jv5afy2cVDpgwRvAhxei4XCJFs4i4ygPVej83eXA4neVF9z0E/DGKcDHlyjeqBDxlRKr94oEUuNIQlfL4/u1dU9c+9YAH10IHNkNNO8GXDYZOOsluLKK8D/nCXh/2OfA6U8BuS2Bsi3AF1cDr54ArPlGyazatRANabl4vP4ipKWnYxMU4XDq/tVBZavJzxisIJs+j9RO0TGo90gF2tJDbxytzBricXewou6QU/n1DLsSuPB9lKLQ/fkdDqx0KC1x0nYvDtlzRJw5UAmtfbN8j/CgBqU52jgdOLQdyGoG9DsXTUmo2Wr6dH4lUw8R8RzlatlqDUkbVjNmLuu/m5wk+Pz+YOMojpHduI3eBzqxrYSwZhWyNc+R6ponj1PH5tliIpq1fr+156i2Aji4Sdz8PZ5Ez9q3sf2qFcC1vwDXzQHyWvksSGlmHFUgB0uyjvUZWqupc4fUHLTY/Py08sDEZwBdfyiaQL90noj7nX8WGiRs+AGvHrkRp6fMQ8u8DHRKPYj/ZjyCFnt/VcIhZ70MDJwEOFKAtd8Ar4wEvrnV0oPlC7fQ1HdYLRjPkQfk+Zl8C+BsAI4ao4x311GeYa7GFGD4NcBNS4FT7lM8G/tWA59cAnyt9AHb0ucG7EeROC42OxTjKO3AGp9v7TZiVM1RhpnmyL8gmwwg6d2hY9At9A7CqKmvVrRWZCPlH+PxULgLqBH5Oa0qwftKCV+lGkcZez3LiEiBtj9BtmTU0S3FRQyFh+dtPqiF1QJK5afwKjHoEiDdvF1S09c5CsA4Ui/a9qg1nmiowq1gLeejymT2HMlUfvUY9LzoTEWyw8ZRHHNAeo6C0K0EElYjqK0HIe0CyobzYu8q0YYAeW1QmU69vR2oSm8GtOkP5DT3uDI0a2Vi1dZhGkYqd6z83NQwqVI1MQPSdwAfXQy4GoF+53ldDUvX+/t1o+D80ww4W/dHEY7glYzn0X3WTXi+/kH0SdmGKhKLX/4tMPhS4JxXlTIDfc5SPhvVraH9CAK6opcLqNmkr1+0gxFke7DkXbf4/IznPBY7L2OFivyN+itw8zLgxNuV51DxzebdsaHbpcpz0lKwOVUJ12UeXBuU58i0CGQAdY70Ojc6BkPKVNv+G9BYKzyV1YWejTKjVecokBIJ8vuXi8ya1KOV//d5GkfUby0YzxF5g0/vp1wAfLRghxYS8ZvKX7YN2DDV7d1qYqwqZLs9Rz7Caur3uFutDp6bEaRn0QSt/ITOOKKyCrK8RjIYR+7knEaP45rO2dQAjfVEho2jOEZqKwLOVAkwrEYMVkXZBOmXTAsVUiiLaDvAXSXbIhslUM8R8W3tAGUBpxDALs8whJzQhjvW4D/O+4GKEqBVH2DCP7220y+yVc17Yc/vv8WLDWcLHVLWhskodpVio7Md3uvzb6C9LiRD5QZ+/y5w8j3K/1T9mDwUAaJfPP2F1ciDFTQV+4FpDyi3T7kXKHR3afe5iFPY8dT7FSPp9CeBSz9DdaOyLXmOtqapxlFpoMZRumXRyUCy1Twy1qrqQmsdoobU0O1kj2OU1s7cjNgZR8aw4nrVOMos3wZUKqFqol49D6mGUaDI0Np3K/Zo7+F3MafWJmTsdz0JKD4KMVuIDYJsXx5WL8/RoeqI6I3E+6kXa/oyH/rv1d9xm0ieI2lga4V1OaQmSPwjIIHRenMFUGFZIo0YfX8xWWBNFuUjqN6RpK9Vg05pHLUZoLm5jW7zQCY/vSCb2FOdAufRaksXE69N9qYpeDfjcaEXQqeRwBXfaZ4qPbRP8gKIJsH9VS483fB7XJvxKFxtBmBF+iCcV/cgtjotmh+P/ItSwfvwDmDuy3733/iZaYEW47JphmJgqWn1HmG1IL47jan3AjWHFA/dsYrgPahFPK8lMPzPQqfkDn+lYLvqOco6sk0JmVpgrGItJ1PT9iE+wmrGWkduoXd6CMbRaA/dTV5Gmt8WNMHirgQfvOeoJi0fm5xtlQd1gn+Zym/VnNeM4d1aoFV+publoIsjn54USlhY8p5y+5imFWJLZNaisYp+IG2ApOZI8xyFWQBSvIZJhWypN6Kh9OfxTASMZV20C9kk8JoFApfBTABBdlCeI+0KzkRzpDOOqKYRXVnQVYVlptoeaRz1t6wBI1NvA/Ec0eJG7lwKS5V3PxPNSHO08jOgWUdFREqej4Mb0HP2/XA4nJibMQIj/vCFpX6CFozcjDRRQE4YR2oa/77CAWi46mq88+Z3OHwk1bqFSEYOcNqDipD5l2dFJpixcKUZ+nRYB4WvqDAlebiol9wZzxtS+TOtM4tmPaEUFaTWFG0HKbM2GVrLKf3eIV7LrIifWVHGQDwcVelFomBnK8chpZCmmoKuR1+LSGbd+eyt5i+spjOOnGoI1TLLbN5rigckLVPRiNH3vmeZ8li3k9CiqiZqIbXgPUeen5+Mn6Wu7uiOPYpxdPTYoIpA6qFzZOKAtnjr160eoUlL1nwNVO4X4W/0nIBYoDWntkzl95+ttlv1HEVCSybPEb3ORq83CjdsFw9kpHpWyJbfhQzLJzshH2WHDh3C/PnzsW/fPjgNReP++Mc/RmLfmBBS+QMW4ekmqUMmxhFd8Q/rUoQ5mw5ieDdvr4yom0PiXi2stsc0rFat6oOs6pjooSt9yryjQo27io9Hs8xCJRX9+7s8tqNp68OG0Zjc5q8Y4UdYSi54xThq1NL4W+Yrlaa1VH4L4+i3zQdRl3kSRrUfqixoPz0issH84RFK3DJLMYwIWth7jEN+Vj9tW8vvjrROZBwRvz6vZKORropKHBDHXi1q1YScVWXi4SDdy1pnR7RKPaQ0UTUxjkjAKmVgWljNpK2G9K74M47kMUfeS5cvw6aqFJh2v2IsGmkzQAjxi3KU9Hb9vkUSTcsViHFkEGST8bPUeRTOo4avuxZ6eY66urYDB1sBLTx1U75Ca9I4kq1wLKFjiRh6GZAa+XEJtaYOIVPzA8lW21suPUfhG0e5Zp6jJKqObeo5SiIxeiCEdJRNnjwZl1xyCSoqKlBQUOBhZdNtNo6iD9WkkH2Vgsl4CtRzRDx74SBs2FuB47qZVLc+sF5J2c8sAJp1QVb6PvV1LTxHAU5opDsi42hfFdD3wveA1f9TQkjkdaGfuiosLz4d9yw9Bidn+jcKpQu+Quc5ktqmHGkcqRk/euhzXPHWAuHFWnbl/yH7vdOBJe8r4SgKZ/nAIz1ZeHlUvQ/t/9c3osXorzRxrb7mkUb5HmD6w8rtDscqJQ1KNyslCwjyAJzy94hrY6jWzhpXJ4zCClVs740UTetrEWnZcfWNWlNUd52jwMJqZKCnqPOIafHGpR8ohhHpy8ibR3W06qqU+7qf4lXSItIFIPWhoWo1WzKwbDVljMjwJONIQIY2WZgOh/AckX7u0ZJ/AC86hXZKhEoprJxiPXZUqLVT8xxRENKn52jrL0q5DUcqMKTpKmIHK8j2GVZTjxHpZYuo5sjEc5QsmVrGC2V5ccNp/AohHWW33347rrzySjz66KPIybFugMlED9J96DUHoda2MEvl13eCN3aDNwupISXF3VjSS1MQuOZIb7gIQ+aYk0S4xMjSuVuBpasCusKRLngKq8nWIaTXEI+le7Zg0LOrrFqbLPc3G4ROFNpa9SXwwz3AH7/WaimZIT9zUXo9sGaycucF7yjP3bsSg5fcB+BqobEydd9//zegthxoPwy48ntFDL7+e0V/tXupUsuJ0vL9Gkf+F3G9Nig9JQXrnB2VByxqPOlF03Lf5fuRIUkLWEaaQzMOAvUc0TEoM2S8vD7kXVmgFrkk41Tq0Qzo09mjElZTj+FANEdGzRV9tlWuTmhMyUAqGclk7LboDldNOZ7OeAUpcLo1VPTTrDMw9HKgZS8gpwWQW6zo6ii87HCIsT93SHs89+MGUfTVNCz78wvAjEeV/3ufARS2R6zQ9FoWYbVAPEeSSITVzLLVkq2vmLxQlvrTZDMO/RHSUbZr1y7cdNNNbBjZII2fFgGzYo+BpvLTlf5hk2w1v2hibMWLogmyrTxHgRpHqgZnv9oaxYxArjYl8iqTrhCtPEeUrSc9HpIdaj85aTx1Ou0hYO0UYMtsYN13QK8JfvdvlGsBUFcBNOuk1CA69w3g9ZPRYvdM3NasD+qHXO795HXfK94yutKnFH3yHlAqfv/zlZ9wu8f78HCQ52itS6l1JMJqqnfDV40j/fvJCZaOx0A1R9IgJ+NIXsl6GTabpitFLCnM2v8Cy9fSe46iEVYLLpXf6DlyoB5pKG/WG0Wly4CdC4VxNGTNk+jgOIADaW1QfPUXwLKPlYKkh7YB0x/yfuHW/YEL3xVh1htHH4XebQtw/FHFHptk1ZUi9cNztQKtQrNG+rQYovccyXONFmV5gZcTgOZIEklBtpyfPLK1ks5zZBBkJ4lx6I+QJPnjxo3DwoXuuDkTuzT+YDLVzNzbFGeXgrzgjKMVbr2HLuTgla2m/p8bYFq1h+fIgmD6/0jjqELnOZLvITVH9PmNxeB2lin9uTRNVlFnYMT1yh2kfTHrVWbYv1Pq1EyqARcqRkZrNSQE4KaGt3D7EMPpRxliU/6q3B5xg9/wnRWa5ihIDweJhje62sNJhhmFMo8oOjI97kKN7u+TFn7p9ZHff7DZakqFbItstfmvK38HXwJkmHhJVPThpUgXgNQfb7SgU00cXxg/f1qK8l2XNhvgDq2tnYIeu76C0+XAh+3uBlr3BcY+Aty2BjjjBeDo8YqujLxIGfnK86j9yL/HCOOKvq9xfdu4PysZHau/xOi19yKFDCMqh0GFTc9/y6ensSm9FGRvy/lGL4b2tSAb56VIhNX0GZayWXYyFYDUh7yl5yjZjEN/hHSUTZw4EXfccQdWr16N/v37Iz3d8+A988wzQ3lZJoyms6FqjmRIjRa3gBcUmuF0NY6U17WocyQrZAd4tReIcSRP4kCucPRhtQOGsFpGiuLZoLEg/Zb+8+8odXuOtGy2E24DFr+ntDYhcTWJok2gK7AWOIwBNQvdxpFk+LWiUrcInbw+Guh/HjD4j0qdpZmPKWUDyNN0sqcIPRiC0hzJYo3pKUhPcaAO6TiS2wWFFZsU3VGBUlNH3xmd0I8VeQHoPckAlYZhoHWO9IJsKU728ByVbgE2TFNuH/Mnn68lNFxZacLIinRfNeNnoWPQqnAjVb2WHhHpOZK90w426w8hud48Q6sA/0bjBGzLG6z7IDmKeJp+jFo0ahdDGXpv/w44/z9Ar4nKY1t/FUZ7mir2drYZiJTz34xJTSMz9B5EOt/IaJSeCjKufRXB9AqrRaB+Va7uNeg8IYMr2bK1Mg2ao2A88slASEfZ1Vcri8LDD6uiUR00UTY2+p+UmQhlqgVrHGlZI41eYuyA01fJ5V9zGEhJB4p7eryud52jwFP5AzWOqoLyHKmC7BrvsBp9XOpmvre8VnguOuqS8nboPEdyjJBVoBgt5N0hQ4a6sJtckdMV8e9Sf0Mq6UjaDQGKldYRAvIgnP0K8N65wP41ipFFP6QtIZG7bIPiw0MS0bCaOjFShWy5gJfl9XAbRz3GeGxv5d3JUo0j+d0EXiHbHVZrVNPgPETqoqGuC+h+akCZXHSxQPsYDc0RfRY6Zmg3aUG1Ct3V6ETH0osnF//9hao3UP2uD+Z0wzOlF+CcQIpAFrQFLp8CfHaFUu2a+v/R8UiFUsngppFKz8G6FmPR/fJ/ISUr9GMoGiEcOXbi2MgKfG6QguxIeo7IaJX7QyF3YRxpnpPEr3HkoTmSqfza5+cKP0RIRwGl7lv9sGHUxE1nwwyrSa9IUCE1KcZu1RtIU4wzd50j81TdQFL59ZqjAz40R9pJHIDBlatuQwXk5CQgjSOiSP3cRlH2Tr3mSJ/NRiLZFj2AqoPAL8+ZvidN+udQyrbRayQhbwz1QqNGsfR4WpZSV4hqIvU918sgaRrPkRJWIw7mqd4Gk4w1qTkyemY0gWuIYTWlfYjB8CIhOmUIEhZeOiPSkxqNsJr0kOn7+5mhF2xLXYesY3Qos50isCZS0jClx8OoRYZmmPqF9GcXfQQMvUIxGslIJ8OIQqHDrkLD9Quwru25Si9BG0FjZ9Q7BpqsYTR0I6E5ov2RxQ6lxyhpNUfqHOAWpCeHceiPoEehvr4eaWlpWLlyZXT2iAmy6WxoniNy+1N2kVUaf0B6IzWk5isbRbs6DCKVP3DNkf/DV15lbj1QqX1O/YItPRdexlGpXnOke4zqxIxRPaa//Qs4vNPrPTMPb8GglE1wItW6+zl5kIRI+3Xg9nWKt2j4dcBEtYluk2lj3FllFFYjDuT28GEcmbf40IwGzTgKLluN9lXq6LTXpuw8yuwq7AT0UIom+qOrmrnVqUV0kkUC0XNJzxGF+WSVbmn8iIfUBsHk9dmT3SOo3moCKvz5u2cBShKgYpjUB/CG+cDvngHy/BcpjRXGFkOBhnFobPQGVCQ8R/o5SYqykzZbzVAEMlAvf6IT9CiQvqhTp07sIYoxB0IoAGnUTZAQLzTjyN02RGLmOaKFWYr9AvUcyUasVLiRTlazicrtOQpckL31YKWH3kgiW07ImlFSnyTDloTM5tPoeTrQ+XglG+in/1Oa1eof3jdFec9mw9Etr5XffUR2s4i2dcjSXfnRWPlaeOVVY5bOc7Qvu7s79EOtJ1TvoFW2mvKenlfhgdY5IqNKZHKpNWyU105T4h1SiH3MlT5r/uh54Iy+OH9IB/PaXBHAaASaYVYAUwqyhbFKhjA1f+1yIhq+Wxu8cURQTOiEW4Djb/ZZVsJOGD1HgaTx63VH7ibWkVm8aU7ar/NgJVsqu6yQrXmOkuzz+yMk/9m9996Le+65B6WlpaE8nYkApSG0DtG7UuUkFZJxtMfEOJKaI53nSF99NtCrMdKbyEnUKrQmJ7NAwmp5qgtelj7Qh9Q8PUduA2iX2qZA4lUHiRYjyioiKPVatrAgXC70P6joPza1jU2rBvqOZTcKf7ojD8+R1ByltVaKezrrFfF5QJ6jFI/sxEA1RxTeKMzO8G4YS9lcNK6pmYpgPUDoOB55VHHE+6oZPaQ+PUeGvmqeniOXUq+IvEdqOrt4PNT9jRPDiNBqoamf2V0d2/95rE/nj1TIVM4fcp5KNuPA6DniVH5PQjrKXnrpJWzcuBHt2rVD586dkZvrKfxbvNi7kzoT+6azBHkHZP8ymqSkcSSNBL9UHgCOqG0a2rjbYLiLQOqNowZt4tcbZf4WSzJgSPNDqfcdm3uHR2Rxw2BS+SVWxpG+v9oOXUhNPCYF2XooxZpq7qz4FPjyOkV/Vb5LhNla1O9GhSsLJW1PRSyQ2hgqT+BPd+SRyq96N8QCTpWod/ymFIOkFHMV8uiZVaCWC5w0xqTRJY0JXxRmp2mGMC18wrCRDYf7nAnkRscLFApmTXYtRe66z04FNmUmm55QGs/GK8YWIsEsxvqMtdwIhX2kN1vOU8mrOUpOzZU/QjrKzj777FCexkQQqc8I1nOkNRmtaxSTVNCeIxlSo15fmfk+w2r6yS+YRo7SOLLSHQVT5t5oHFmF1Up1niNpHNHY0jh7hdUkp9wHrP4a2LdK+dHxUeMpKMx2j08sFnEyjowCeSvjSBaBJOrJOCKDSBhHpC28wG9YzSgCD1SQbTz2RKYahdTWfKPcQXoaG+HuLu8rrOb92T08Rzoa1HBiRqCC7DjG2Hw2qLCa7hjJi5LmKFl7qxnrTiWL58wfIR1lDzzwQChPYyIEeX1KQ9QceRhHDY0ihT0o48gkpCZf06jFqKoNTSPgr0p2VX3gJ3GeH89RkYnnSGaq9WtfiNnr91s2phWFIX//jlI1O7+t0p6hoAOu/2YvpmxPxYsxdE8HWgjS3eYjVbuSFN4NKlgpe3NRcUrKkvIRVjO+X6AVso3FG4XRRQb44e1AWraSwm8jQvYcaWPraRxJrVVyeI48NS7BlPnQZ0dGIltNvK+uJyCRbHWOvLLV1L8cVlNgWXocQgu5vACVno/gJ6l6j7Ba4J4j70w1D8+RTnMkNQXBZn/4y1iTjT8DOYmN27TK9+wVZ5atJmsc9W9fIIwjGiOqomuqYyFxNv3o2OmkNP7DMZ1kNGPFr+bIXQRS8xzRgk2Cc0eK0kH+xaHAaQ8AAy7SjCNjKr9M/6X3I+OKDPiQPEf0urIf3VGnKgURbYR7XP2n8ksvk15TVK+G0SQymzBkzVEcYcxoDabvot5zFLlsNdU4UkPFyVohu1Y9BrWwGhtHgpCOspQUKqBlfTJzJlt0kV4jWtiDznLxqJIdgiBby1QbaP6aHmE1WeMoLcLGkWp0RcBz1EzWOdLVMpLVsfu3Vwo80jpPWptAxyjYwpexyqoyLuRuzZETaNVXqafz/V1KX7OvrhPZY32rJyLXkYvi8kJgR4bSRqVVb4+wmr7zunJcOIM0jtSQWm/7VdoPpIaU3uCUpMqwmsFzJDVHoZzH8YaxxlowFZml5oiMyEC8kYGQK/urGQTZyWIcSc9RndrvTkt0SZLP74+QZu8vv/zSq/bRkiVL8M477+Chh0yaJTIRRWZehaI3MgojgzKO6iqBA2r2kqHvl5nnKNTsB2nAmGWr0UkcSiq/peZIHUO950j2VevWMk/sO30O8tYFahwFo6WIFoEWgpQ1eUT7EOMC3nM80H00MO9VYNZTwO4leAVLABpCVS8tKOqKnN4fKu8nwrVOjwm40U+tJb1XoFtKiVI5PCUNODqw2kZNidZg2We2mrfnyEqQLcNqyWEceQqAtfkhPfBsNTqfg9Ev+kIrXGoUZCdJEUSPsi6NzqSr8xQV4+iss7xFkueffz769u2LTz75BFddFbmaLYyPprO5wWWqmV3BubPVAjC0KHOJqvJSobl8z2Jz7sazzrA1RzIDz8xzRPssQ4qBnMR+NUfqwiw1WLT/srlq+2bZImxZVVcttFmdA0yacqcoxzCsZqg7ZIZn+IvCarIWj867kZap1NIZOAkN0/8PZYu/ggsOFBfmIoUKYlK/r7It6FX+G7WMVz1Hje6SApQZ6ceRLL13xDE1aid5SnXPLoLdCKjOkYnnyEPsrkMaSwFXyI5j3HWOPAXAgWiIpOcokpXPc4yeI6k5ShLPiWdZF6d2IcWaI4WImsjHHXccpk+fHsmXZHyk8YfrOaIJPijPES2U/X8P9PpdQFfU0dAc6V8/EPcvfVbZMZ4mA+PnpDCOfJwMIJmpRpXHyajTusabpfNbYIcGjrLuUCDhH60IpDoOMtTjQV4rlJ7yJI6pfQXD6/4F3LIKuHkZcNy14uH+ez7T3i/QGkcS/XcyoHy2csPkGLMDgRidpp4jdSFqtBBkS69dIhNOWE0eI5FcuOVrJa3mSHd+0oWsPBaT5fP7I2JmeHV1NV544QW0b98+Ui/J+O2rFqJxpC6cVAVaeg4CMo5IhH3eGxav6ZmJQmgVbYM1jnTZahRG07vRA+3kLaHn0vuTN4iMLqNLnv4nzwWNBXnkZKZaB7W+klkdJF/QeMrCfnbXHOkfI8PRKqNKIsXYWi0iYshlwK/Po/3BOejg+D2q61ppoVXNc1J5AO3K5iHl13XAoa3AwU1ARQlw8t3AwIu0Y68NDqJdJXknHe5u8zZD85Aa2uTokd5TfXVwf4LsZAiraYJsQ3ZYIAZPn3YF4hgd2LFZxPZHE2Qbe6slieeE5j4aUwqpac21k8hz5o+QZu+ioiKPRYYWsCNHjiAnJwfvv682imSi7jkKtums8QpOemaoB1Qgxfp8IStk04lGBgJ5Y9zZKKEJssnIIKNGb7iFUsWWFnN6HdmaxAjpjsg4It2R1Bt1KMo2GEeBeY7kZ4655igAD4e8gpfhL3e2mrlGyJ2ppjOkW3QHuo2GY/MMXJT6E36t6+VZ56d8D9JePx7HUKPerYYX/Op6ILclmuUMFv+OTV2o3N/xWCC/DeyIe1x9ZKuZ9JWTIUtvQbaayq9qkhIZaSxKnVsw80PnFrlYeN9pyIvgBUeusUK21rMxeYwDOkZpzpYXf2TDR0rwHu+EdKQ9++yzHsYRZa+1bNkSw4cPF4YTE120GkdhhtWoAjVBxke4Ike9sUJGjShCqGmOUoN+LQp30WJMBpyHcRSC2FkWezOKsb1rHdVrnqOORdJzlBGUcST3L9aTTCB1joy1iDTRsEEX410A0jBtDLsC2DwDF6bOxMy6Kz1f9/u/wVF1EFXpzZHVawxSinsAzbsC674DVn4G/PcytDz7C7H9uBTVOOp9BuxKYB45k/YhFiFLqTlKjrCahSA7wHPZwyiPoKFLRppHokcSGUd0YYxat2yAPnukBO9JaRydcsop6Nixo+kgbt++XTSmZaKfrRZyWE0aR+U1wfdVs0C/ENDCQRNPqJ4j6T2SxtFRrZQChEQoE5gUhBvF2BJpAJHnSGqOOjZXPUea5iiwsJoUd9JnjuUkE0i2mlYAUt02UM+Rlyi25wTUZbVEy5r9GFw1B7UNSruRE1wLgdX/g8uRinndb8MJZ16LlPR0twF0pATY9gs6TLkMPR03YXjKGlvrjQIXZJt5jnQ1pHTUJVURSKMgO7YC4Fyd54i8J/KawF+z5ET8TmQXgED6VSYLIZ2RXbt2xf791M/Yk4MHD4rHGPu2DtGuFnSeI322UKhQGE1e/Uo9httQCH6ysaqS7U43Dfwkls1n/XmOyirrtAKQHTTPUWhhtVjrFoLKqlKPB3e2mrlxVGFRHRup6TjY80Jxc1zNdyKsloMa3Fj9qrjPedz1KM/u5C3uv+h9oPhopFbsxmcZDyHN4URlUW/Fs2RTMkNsPGvZWy2JPEfGxrOaIDuAVP5oIDVHlDhSowuTJp3nSHfxlyxlDAIhpJEgF6QZFRUVyMryrEDMRJ6DFaE1nTVqjvYdiZznyCydXxoyuSF6jogDhow194Qa+KHbWq2K3cmkia1nrSN9WC3bEFari5saRwFrjjTPkQyrmRcqlJRb9FUjjvS5GE6XA8Ocy5FWtgm3pn2GVs79QLNOcJ7wV4udLAIu+VTojvIdyrhXdhsPOxOMR06v47Psrab+n55UniPPCtmRagcSep2jRu2CTn+RlwzItUBe/CWTYeiPoFat2267TfylcMH9998vBNj6qtjz5s3DoEGDgnlJJkjoSpMW8Uik8ktBdqSMI3JHUyVpuThUqimy8gotpHR+g+colIySO8b3xPBuzTFxQFvTx2ULlk37KzTjq700joJM5bdDdexANUdSGCuNWs1zZKk5svAc0eLeogtmOAfh1NQl6LXsUZyYSi1UAEx8BsjItd7Roi7ApI9R95/TkeaqR+HQ82FnghG6ezaeteqtljztQzJ1F0/BFnONBrmyzlFto4cYO5k0N/LCSNMccVhNI6iRoCrYBB3YK1asQEaGe3Gm2wMHDsRf/2pxlchEBGkY0fkbSl81/Qkh18BCNXQULsbms+FoCqwKQYbiim9bmI0Lj7HWwcmw2oqdh8Xf1gWZ2kQerCA71joKbw+HM3DPkVYh27fmyMxzRO/3YeMpwjhqs+9nkY0/P/dkHNtjDJXQ972zHYYh488/wVWxH5nt+iGeQkOBeo40r1wSp/Lr2xYpBhJieiGheY7qG7WabMmWxi4LQcpU/mA88olOUEfljBkzxN8rrrgCzz//PAoKCqK1X4yfNH4yjGTxwmAxNgONWFhNKwQZfKpuoIUgo3G1KY1MSufXZ6qFUudIhp4i1RwzVOT41ATk4ZDGkb86RxbZaqpxNMM5GLtcLdDecRDlrhx82fovODbQHW7Tn+wp26MZnSF6joyCbDnWSWEcySKQ9U6PkhexCuXo5yXZWzHZNDfSYJWC7Fh7vO1ESEfCW2+9JQyjjRs34ocffhAFIH1pkZjIUSoz1UIMqRHGFPPIGUfyqtrTc5QbQeNIXpXnRHBClZojScfm3sYRXVk5LcJNekoOKzqutgVZcaSNSfVZqDCQsFpWRgqcSMErDWeKvw/UXyYy2BKNgEokmGmO/HiOkqJ9iOY5IuPIPUahXuSFC723jKDJi87sJPUcaYLsJPv8ETeOSktLceqpp+Loo4/GhAkTsGfPHnE/9VS7/fbbQ3lJJkAOhJmp1hTGkfQchaU5sshWi0Y2mAyrSWQBSP3YkF0kjQNf7FIF3e2auV8jXuocWeliAimjQJMsLXLvN47BAwN+wpfOEz16iyUKmkcu2DpHxqa+RkF2MhSB1IXd7aDNU6rnp3mUR0k248BLkJ0k1cEDIaQz8pZbbkF6erqoaaQXZV944YX4/vvvQ3lJJkBKw8xUM6vjIb0jEWsPYPAchaK/kWn3lJknW5zoKxNH8iQ2Nt3Vh9Vo8pD7H0ito92Hqz0E3fEkHPanOZLfq5kugxYaubCU1rib2SYashK8aIBs4Uk0rXOUYl4mIak8R7reatpFToyNEXmelKqeo6TTHBnrHCXZ5/dFSLPX1KlT8cQTT6BDhw4e9/fo0QPbtm0L5SWZAJG6mFALQEbVc6RlozSKKtnyqjiUq0PyjJHLm15C1nUiqusjP6ka6zx1UAtAGjVJgYiydx2SniN7hNUC6a0mjVptAbdc9H03lJULi5xojdq2REBvlFv1VzOtc2SSyk8yBHfj2cQzJH1dPGkh9xil8Utk30fZrzLZPCfyXKYs42T8/L4I6YysrKz08Bjpw22ZmaF7NJjAjaPwwmrREWTLMAotDuH2GKMQT4tc5ViShRmj1f+I3qtAp6PRe4704+MvnZ8Wu92qcdQ+xmG1QDRHwXqOZENdebXp9Z6qmFV62BLTc+Q+7qy8coH2VtN7RNOTznMUfDHXaJCd5GE147mcbJ/fFyHNXieeeCLeffddD5e60+nEk08+idGjR4fykkyQBSBDbTpr7jkK3dCy8hzJ6th08oV6VTy4k9KB+7fNB7X73JNqZE9iKcom3UzbQk+vT6AZa+Thkl6DNobXaGpIIC2NI6tECeMi7k9zZJaFpSdHLa8gM38SUXNEDXo17YxFOn+gvdX0XqRkah+iaI5UPWK6PTxHMqyWbMaB8Vxmz5GbkMz2p556SvRXW7hwIerq6nDnnXdi1apVwnP066+/hvKSTBM1nTW7WohkEUjtylCKscM42Y7v3gLTVu/FnI0Hcf3JR4n7otUckkJn2w5WCcPIuFAF2kJk96EaTS8V65CSHB+yi6hvlNn+UEp1MNlqmjFlYfRkqd+1rJkS6zGIFjRedIybeY7IEK0xGSczQTZ9L9rjKcmZrRbrsJpsSi098vIYThaMa0Gs67PZiaAvV+rr63HTTTdh8uTJOOGEE3DWWWeJMNu5554rikR27949OnvKeMTGI5XKT4uoVZgk9DpHOk1BGG7zE3oUi78LtpZq+photeeQGWvGkFowhSDdeqPYhtS8GgHr+kb58hz5q3MkjSmrcJksIFehGsaJGFbzp+ciDZF01HnUOTIRZOvHORk0R3I8aHy0ooMxDqtJz5UskaIPmyYDxnM02QTpvgj6yKQsteXLl6OoqAj33ntvsE9nwuSAFlYLwzjSnQCRylQzpvLLirPhGDHdW+YJLww1yF28vQwjuxdrnqNIX+FJ0bU+jd8o2C7zE1azi95ILrakY6HFmsasEOnWxo4UZOtEw+QBMbZRkJ4Oa+PI8ztJWOPIRzq/XqTtUSHbRJAttV3kNIpVrZ+mRD8e8lyKdVhNlhlxC5IT85i1gjVH1oR0JFx66aX4z3/+E8pTmTAgQWy5WmtHipVDQb9oRSqk5qE5omyUWtXDE0alaFqcjz9K8R79uvGA+CuNo0hPqke1zhN/B3Qo9HpMXwgyHjLVAq11JDVEcjt9rR1jJWdPz5H52Bv1CsaSEYmCPH/MxlWOEdmVssCelZ5LZgUmg96I0I9HmRrGirXGJdfguUo248B4AcNhNTchrVwNDQ1488038eOPP2Lo0KHIzfVsLPnMM8+E8rJMgHojusoMx6jRnxAFkTSOdGE1zXMU5mRDxtGXS3bh140Hccc4XbZahE/ia07shhOOKkbfdoU+wmrx4zmSEz0VrrTKqpKeDy2slub2XpBwOEN37USeJLMsLM/3S0sqz5HZuOrHVO95SzfRc9Wrxql8LNGh8aBxIaO8VBXtx1xzZJhHki2sZDxHk804jLhxtHLlSgwZMkTcXr9+vcdjydTRuKmRKe0kGqasmYiE1SJoHMkTja6e5cIR7uR3/FEtxN/lOw+JvmWa5yjCxhFdvQ/ooGTHWYfV/Amy7aM58ljE/XiOpCdI6mJMe4A5XVqjYmvPUUpyGEc+PHJWhTKld4j0NlQ8ks5fmbmWnqDjZIY0juSFRqx7eRnfP9aerKaGs9WsCenIlA1omaaFsqmIzi28RcO2CKule6fyhzv5tS3MRrfiXGw+UIl5m0t1PZma7iSWniP/YbUaexlHfgpBuhdyKcjWeY4MtY5kjSNf2WremqPEnGjl55QhNLM0fqNhqK+ATd6jzJRUzQDVG6WJDp23JA2QmqNYeyqMF2+x3p+Ya47YONJInrMyAdheqhhHnZp7hjHtZhzpU/kj4TYfqXqPft6wX1ukm3ISC6TOERkgUixvl7Ca9BBah9U8PUfk9ZXCYL1wWO9lMmpHfBpHCVjnyJ+Wy9JzpPP0St2R/JsMBSCNx4T0wsY6rGY0BrKTXXNkCI0nM4k5eyUo2w9Wir+ddF3jQ0F/RR/ZbDW95kjWIwr/ZCMtEDF9zT7tvqZ0x+sF2Vb9tPYcrtHCfZEc03CQqfXWYTWzHmCqNsbgOZLb0kJuFdI1pmUnaljNp3Fk5TnSeYekUVSXRH3VvBudSkF2bBfjXMP7J3udI1k8lokT42jr1q246qqr0LVrV2RnZ4taSg888IAoQKmHSgxQ9e6srCx07NhRVOw28umnn6JXr15im/79+2PKlCmIF7aVRiasRguclIZF0nMkPRWUrVatCrIjcWV4XLcWYn9lNlhTL7xyjMguIoGzP72RXXR3/lqIaJojj5Rz81pH/jLVlPczao4Sc6GR2ipfqfxGz5HeOyRF2TJ0mQw1joznrbzGiHUqP3uOkvvz+yIuzsq1a9eK9iSvvfaaqMT97LPP4tVXX8U999yjbVNeXo6xY8eic+fOWLRokaji/eCDD+L111/XtpkzZw4mTZokDC0qWHn22WeLHxKYxwM7tLBaTkSyRiKerZamr3MUGc2R1Pz002WR0QkcjiA9lAlECsBl3zA7F4AMpB6P/n6PYoVaPR6j58h3jSP9+5nVtUkk5HFuZnRqrUMMi45HyFKG1VQLQV9CIdExGo2yzlCsyE3yVH6uc2RNXAQYx48fL34k3bp1w7p16/DKK6/gn//8p7jvgw8+EJ4kKjGQkZGBvn37YunSpaKswDXXXCO2ef7558Xr3HHHHeL/Rx55BNOmTcNLL70kjC07Q1WHZXPETmF6jqRuhCZyKTaObONZXe+kCLmpKaV/xa7DMRMNUpHIqrpqUSW7syKB8mBXmUzjt0eNI4/wT52/OkcpJpWcXUE1ndW/X+J7jlSj02RcfbVYoZAlNZuVhmd9UobVjHV1YpytZhRkJ1lYTf990JqQLDW3EsY4MuPw4cNo3ry59v/cuXMxatQoYRhJxo0bhyeeeAJlZWWiojdtc9ttt3m8Dm3z1VdfWb5PbW2t+NF7qGQbFfqJJPL1zF53894jWpuL7FTzbYKBJgHKGsnPcETsc6TBpRlHFTVqf60I7CsxvEszvDrLHb4J9zV9jbUZBVlp2EUVyo9Uo77eWxC/s0zRg7XJz4z4cREqmeqiW1ljfqzWqp6PFDi1x+VcWVPr+ZzKmlptArX6fEa5QioaPc4Tu4xLuMjPWVnb4PWZaKzFNlSd3PAYGUGUpyDHlv4StB5FamzsPtZG8XmGwxXTfaX315PmcJ8L8T7WgUDnvj5cbNfPUh+hsQ7m+XFpHG3cuBEvvvii5jUiSkpKhCZJT+vWrbXHyDiiv/I+/TZ0vxWPPfYYHnroIa/7p06dipyc8D04ZpA3y8iygzSppKIgpS4iOqmTix3YluXAtqW/YscyRIR9wnmShorqWuwqocXUgXWrlmNKSfhvQBfpqY5UNLocaKitjphWzGyszWioohUxBTPnLEDFBm9R9opNyuP7t63DlClrYQf27FT2adW6DZhSs87jMaq3U1NPV8kO/DprJgrUa4r6WuW+2b/8gu357u3XHVaOv7rqSsuxX3dI2UYy48dpmrEVzFjbnc17lM+5edsOTJmyzeOxJepjpfv3eo2Tq1EZ2+kzZqJNDrBUPacrDh+OuPbRrmNddkA5JiW//TobG2LobD1Y47kM6s+FeB/rYOZsQWO97TW408Ic66oqRZpie+PorrvuEp4dX6xZs0YIqCW7du0SobELLrgAV199ddT38e677/bwNpHniMTepG8qKCiI6HuRVUtf/pgxY0QPOz27f9lKFTfRr2tbTJgwIOz3moDIQxlb/1g6G41IQWZeHnDkCE447hiMUhvIhsvn+xfgty1laFlUiAkTjovaWJvxXfkybFi1F1179sWE4zp5Pf7s+l/o1MP4UcMxvKvboxlL1v24ETP3bEa7jp0xYUJvrzCZ67cfxe0J48Zo2rPn1v+Cg7VVOGb4CBzTpUjbPnvdfmD1EhQ3tx77NtsP4V9r5mv/nzHxdKG1CXas7U75gp34cutqNG/ZGhMmDPZ4bOfPW4CtG9ClUwdMmNDP47GHl89EVUMdRp5wInq1yYdz+R5g/Qq0Km6OCROOici+2X2sp1euwPLSPdr/E8edhuZhNNEOl4OVdXh4yUz3/owfi/ystIQY60AgreQ/lv4sbjfPz8WECSfAjtRHaKxl5Mf2xtHtt9+Oyy+/3Oc2pC+S7N69G6NHj8bIkSM9hNZEmzZtsHfvXo/75P/0mK9t5ONmZGZmih8j9AVF64Qwe+2daoHBrsV5tj0R87Jdml6lQu2tlp+dGbH9PaFHS2EcUb+2SL1moN9j8zzlGCivbfTantL7d6up/J2L823z/eRmKftR2+jy2qeaRrd7OVd8R2p/NdXV43KkeDzHCYemI7L6fHnZGR5aBn2IO9rnTFOSl209rrIuJGlpjI9pWWkOZQxpjMX9PsY0VOw61sbU/cLcLO3YiwWFOZ6x4PyczKCzB+061oGQm6UPq0VuXo0W4Y51MM+NqXHUsmVL8RMI5DEiw4h6ub311ltIMWR4jBgxAvfee6+wMOUAkKXZs2dPEVKT20yfPh233HKL9jzahu6PmwKQERBjN2nX7QgKHM8Z0gHfLN+Dcwa3R1MjW4iQINvs6pM8MZTB36bQPoJsdyq/dSVn7zpHUpBtka3mIwNNn+mSqDWO/FUeN7Zk0SOF1zKVvz4ZU/l1xw+dL7E+TmjOov2gMDPpoZLpuzAmWCSbGN0fcXEkkGF08skno1OnTkJntH//fqET0muFLr74YnGlSmn6lO7/ySefiOw0fUjs5ptvxvfff4+nn35alAegVP+FCxfixhtvRNy0DgkzjT+a6BcEWQ8oNzNy9jdVnv7+llGYdKx3WKspC0Fa1ThqnZ9lq8nVV4NUfQFIjwapaaHXOdJnHun79yVTEUhpMJmVMTDWkKpPxgrZusU4NyMt5jXB6P1pP5Kx6azx+4h0v8p4Jy4E2eTdIRE2/XTo0MHjMeoWThQWFgqR9A033CC8S8XFxbj//vu1NH6CwnEffvgh/v73v4saST169BCZav36eWoD7AYVi5N1dOzsOaI6LjTR69PAcxPkhJMlD6RHzLwApH28RoF7ODwXcdkh3rvOkXc1bav387ddvOOrRIK7PIKJ58gwtrIIZDKlT+uNa7t4Kmg/qFRKMtb40bcCSkbjMO6NI9Il+dMmEQMGDMDPPyviMitIyE0/8cTuQzWiPgq5QMk7YWeo+F19Y4PtJsBohtXsWAAycA+HsXu8bB9i3lvNZ50jXS5/IhtHbqPTLFxpbURKI8i7CGTyeI70HjW7eCroAm5/As1VwUDFdMlAolY2dvk+7ELizmAJxLZSd0+1pqwMHQrGcEqsi7xF2nNkFlaTxlH7InsZR77DauYaIi30E0KFbJpk5eGZqAUg/VUel+HHQDxH7t5qSeo5somnQs5RdtmfpkZe8CTr57ciec7KOEYTY9tYb2R2ZUi3ZcuEeEdqjmTDTLOwGmmibOnhUENigWiI3I1nzT1Hvowe0m/IhcaXcDuR24f4Cj8avXLSg2QnnVq00R8XkdQjhoP0mCRrWEkeq8n6+a1InrMyjtl+MJ6MI/cJlpsgXiOjIJtS941hT6JdoU2NIx+CbKNw2Bj6MW7vL1wmv/9EDqvJ8CEZR1Lz6NVbzWShkT3UtLCalq2WGBcQ8SoAptIgyew5kZ4ju3wfdiFxZ7AEQstUs7EYW6JfbBMphl+oao7ILpKZeHbXHMnu8b4apBo9QXKh9gqrye39eITkeyZ0WE1dRMkukqExf0anWVPfetXIluUTkgG90WgXYyRH3Y9Emq9CMVjt8n3YheQ5K+OYbXEUVtMvirkJ5DmizyWvrA5Vu0NrpOcprayzpebIlyDbyhNk2XhWNQIyUn1PoNnJ4DnSLSI1dc6AjE69V06ObX1DcnuObBNWU5vPZie75ihJjUMrEncGSxDIbb+jND49R8aO1/FOkZbO7xZl7z6seI3yMtNEc1q7ZlUZQ4FWKeead6MxRM+RNI4SeKEhjZDUZhkNT2pGa7XQyKy0RpnK70xCzZENU/lzk7jOkf47scv3YReS56yMU8grQTU4qFZah6I4MI4S1HOkD63pRdn6GkexLmhnRD/ZSWNI+98i5VzTxThD0xzJ90xkz5FVDSm6kCkpV/RnbQqy/AqyZYVseX/SaY5sYoy4BdmJfcz6+05Yc+RJch4NcRhSo8k2Hq5sPDQFCXaymVXJ3lVmT72R0VA1ejisUvPdC7hVKj+H1YgsWSZBN67lNQ2oUsXvZm1kZMhSeuWSM1vNffzYZTEedXRLFOdlir/JyIAOzURot3fbyDZSj3cS69I+gTPVOsaB3sgrVdcmk1+kjaMyVWNk5zR+gmpikZFCho21cWQUZJv3VqPecf6KQOoN4ngw5MNBehn041qiNh+m48S0zpEmyDZ4jhKk3EXQniObaI6OP6oYC+491Xae36bivt/1xm1jjxbSAMZN8lyyxHmNIzv3VNOjXxTsMvlFuhDkIb3nSKbx29A48lUI0qoHmFaokFP5gy6T4CukZiZ2l9lqyeQ5smOFbCJZDSP52dkw8oZHxObEUxq/d2NJ+0x+kWwh8t0KpeFx95Z5WL/3iG09R3IRP4R6r2rO7grZBs+R+v1ZF4H0vZC3UtvbNM9VDMlExazAZokqzjcLqXmUSdDCasmYrWa/VH6GMYONI5uzXW0dEi9hNU/NUWIdXt1a5om/6/YeET96bOs5skjntxZk+6tz5HtBu2ZUN3QrzsWEAW2RyLibz7rHqeRwrfjb1sI48g6rqXWOkshzZMcK2QxjBh+dceM5ykU84JmtllhXhucObo/WBZlYvbscm/ZXYNP+SmzcV4FW+Zno174grjrIW1VyNtbi8a5z5HshJ4/R74/piETHrIZUSbniOWrtJ6ymFYFMSs1R4iZsMIkFG0c2hha0fUdq40xzZD/BZSQFzif2aCl+9OnbdtYraJojr7CaRRFIqzpHcvskTXcOJJV/jyrItvQcGfRc0kjyJ3JPJOyYys8wZiTPWRmH7ChTvEb5mWlaplR89VZL/MnPzoaR3li11BwFWudIq/zMU4be6KwxyVaz9BwZK2Q3Jl/7EM/eaol18cQkFslzVsZxSK1TixzbL8J2z0ZJVjTNkUW2mlFDFG6do2TBLFwps9XaWjQgNvata0jCIpA0j2m9vHh+YGwMm+7xkMYfJ5lqXqn8fGVo2/5q1kUgPTvHG+scsefIvM4RGZuH1LYyVtlqXqn8WhHI5DGOiDMGthNavXia15jkg1cvG7P9YHxlqnk3luQrQ9tmq1kVgTTJViNdVaB1jpIFfd86fUiN7rfqsWfUc0nvXDLVOSL+ecHAWO8Cw/gluc7KOGNvea2ta+j4bw/AtrdttDGBFoE0yVYj/ZGUIHFYzdzodIfUrHvsSQ9RozqYUteVTJojhokX+Ky0MVXqxBtPRoY+lZ81R3HoOTLoYvTbiu05W80jXCmNTH9ibI+wmjSOkrAIJMPECzzT2Rh5tR9PRoanIDt+jLrk0xyZp+ZrC3iDy6tgZCB1jpIF2XhWGkf+0vjNw2rJVwSSYeIFPittTFV9Q9yV2fdI5WfNkY16q5lXvNZ7+jyy1XSeozqdh4NqPTHeHrm9alittS/jyEuQzZ4jhrErbBzZGJkmHE8dzuW+kuzCuPAy9ihWqP/f6DnKMMlWc9c44u/TqkTCHrWvWkCeI5nKn4SNZxkmXuC4h42RmTDxFFajVhpUtJLSmdnLYF/jyDqV37vOUaBNZ5MJY3HNEjV5oo0PzZG78awraduHMEy8wMaRjamqU8NqcWQcUTPJGXeczAupzbQxes2Rkppv0VvNpEI2p/EHkspf7bPGkWdYLblT+RkmHmDjyMbIBS2eNEdEcV5mrHeB8ZGt5pF9ZmwfYtJbTRaATKYeYMEYnTRW+9UeiL6MI69Ufq0IJI8rw9gNPittitPp0q5K48lzxNi/fYincZTqt84Rtw7xRurpyDjaX1Er6kBReKw41/rCIFWXyk/eO63OEQuyGcZ2sHFkU2rUUEY8eo4Y+5Cd4d14VobJSOpizJTSOsd71DkyF28nM/rGs3t0NY586ez0qfz6sKVs9sswjH3gs9Km6K/04ylbjbF/nSN99pmxmnO6z2w1ni7MhO57NePIdzhZGkE0tvrxZc8Rw9gPnu1silzMaEFK5WwWJqJhNWtPkFm2mqxzxJoj73Gl8OOOMqVBdNtC321+9DWk5JgSrDliGPvBZ6VNkYsZ642YyIR/3ItxjQ9PULpZthrXOfJCb1huPVjlV4xtTOXXC965CCTD2A82jmxKvGaqMfZCHj/kqZALsvQcmYVr3boYTuX3BY2FjEhuPVDpt8aRR5kEneaIvMJWjWoZhokdPNvZFPYcMZFAbwDVqFlnvjRE+tAPZVSJ7bkIpBdk0EjDc4s0jvx4jtwVsl1cAJJhbA7Pdjalij1HTIQ9HNLg9pWaL8NqZBfJejxye9YceSLPTZmt5tc40oUsZakEbuTLMPaEi0DalBp1IYun1iGMfT0cVXWNeOmnDWjXLBvbS6s8WmDo0WdO0SJO9hPXOTLHGJb0G1bTid1liJMz1RjGnrBxZHPNEafxM5GoWE4G0Ttzt3ncb3Zs6TOnaBGnbVhzZI7RuKQ6R4Gm8kvPkSy6yTCMvWDjyKbQlT7BYTUmXP51yRBMXb0X5dX1OKz+UH2eq07o6tM4kqJsTaPERSA90OsBi/My/IYd3ZojEmSrfdVYc8QwtoSNI5siKxpzWI0Jl37tC8VPICjZU4rmiETZBIfVfLcQCURv5BlWcwuy09kbxzC2hM9Mm8LZakys0Id/CG48a47+3PSnNzK2CZHeOM5WYxh7wrOdzbPVWHPENDXGWkesOTJHf24G4jlK1YmvZe9Ero7NMPaEz0ybe444rMY0NdKbwWE13+j1gMF6jqSmkLPVGMaesHFkc80RC7KZpsbYfJaLQPrPVmvjp6+a0RCSFz/sOWIYe8Jnpk2RV5YcVmOaGmPz2To1BMSaI0/0Fy5tAxFk6/RF8uJH701iGMY+8Jlp8zpHORmcUMg0LfpKzgR7jszJ0oW8/dU4kgU5pYEkz28OqzGMPeHZzu5htQz+ipimxd093tCLjb2YYaXy640ht+aIz2+GsSN8ZtoULgLJxAq5YMsqzpyt5juVPz8zDXmZgXl4ZRhNeo4y2HPEMLaEZzvb1znisBoTo2w1qTlS/7LmyBN54RKo10ifzu+uc8RjyjB2hM9Mm8LZakyskEaQbHGhhdXYOPIgP0u5cKFmvoEijSF58cOaI4axJ+yWsHlYjescMbHzHBkF2Xws6jmtT2tcPrILzhzULmg9lyzyyqn8DGNP2DiyKVKTwKn8TKw0R1wh2zcFWel48My+QT1HeorcdY7Yc8QwdoRnO5vCvdWYmGerOZ1wuVycyh9BpCBbhs05W41h7AmfmTaEUqilCDaHPUdMEyN1MRRWo1pHLsWBxGG1CKB5jrQikOw5Yhg7wsaRDalRr9QJ9hwxsaxzJL1GRKauXQYTGt6CbB5ThrEjfGbaEDlxOhwcymBi6DlyulCrejiIDF7II+Y50tqH8JgyjC2JmzPzzDPPRKdOnZCVlYW2bdviD3/4A3bv3u2xzfLly3HiiSeKbTp27Ignn3zS63U+/fRT9OrVS2zTv39/TJkyBXajWpfGTy0HGCYWC7jec0SGUQqHgMLG2D6EBdkMY0/ixjgaPXo0/vvf/2LdunX4/PPPsWnTJpx//vna4+Xl5Rg7diw6d+6MRYsW4amnnsKDDz6I119/Xdtmzpw5mDRpEq666iosWbIEZ599tvhZuXIl7ATXOGJiSbouW61OGkfswYwIMoym9VbjIpAMY0viJpX/1ltv1W6TAXTXXXcJw6a+vh7p6en44IMPUFdXhzfffBMZGRno27cvli5dimeeeQbXXHONeN7zzz+P8ePH44477hD/P/LII5g2bRpeeuklvPrqq7BbjSNO42diWufI6fYccXg3Mmh1jrgIJMPYmrgxjvSUlpYKY2jkyJHCMCLmzp2LUaNGCcNIMm7cODzxxBMoKytDUVGR2Oa2227zeC3a5quvvrJ8r9raWvGj91ARZJTRTySRr1dRXSf+ZqenRPw9GAU5rjy+3sjoWW1dAyprajXPUahjxWPtRtpC0iOX6nBFdFx4rJsOHuv4G+tgnh9XxtHf/vY34eWpqqrCcccdh2+++UZ7rKSkBF27dvXYvnXr1tpjZBzRX3mffhu634rHHnsMDz30kNf9U6dORU5ODqLB3AWLaNpEbVWFLTVRiQR5DhlPdu8gL1EK1q7bANfedWKaaKitDvtY5LEGSg8oYytZv3YNphxeHfH34bFuOnis42esyXaIC+OIQmPk2fHFmjVrhICaoHAY6YW2bdsmDJY//vGPwkCKpmj57rvv9vA2keeIxN6kbyooKIjoe5FVS19+z74DgLWr0KZlc0yYcExE34PxHOsxY8Zo3kdGYcmUtfh573Z07tYNQ7u3AFYtQlFBPiZMGBnS6/FYu/nm0FKsLNun/T+gfz9MOLZjxF6fx7rp4LGOv7GWkR/bG0e33347Lr/8cp/bdOvWTbtdXFwsfo4++mj07t1bGCm//fYbRowYgTZt2mDv3r0ez5X/02Pyr9k28nEzMjMzxY8R+oKidUKofT6Rm5nGJ12Uieb3GK9kZijTgtPlQCOUC4+sjNSwx4nHGsgw6Aiz0qNzjvNYNx081vEz1sE8N6bGUcuWLcVPKDhlx3BVD0QG0r333qsJtAnhhenZU4TU5DbTp0/HLbfcor0ObUP32wnOVmPs0OKCqmPXqpY6C7Ijg7EiNtc5Yhh7Ehdn5rx584TWiLLPKKT2008/iZT87t27a4bNxRdfLMTYFHZbtWoVPvnkE5Gdpg+J3Xzzzfj+++/x9NNPY+3atSLVf+HChbjxxhthJ2THbq6OzcQCmUFVr6tzxK1DIoOxIjZnqzGMPYkL44iEz1988QVOPfVU4QkiA2jAgAGYNWuWFvIqLCwUIuktW7Zg6NChImR3//33a2n8BGW3ffjhh6L20cCBA/HZZ5+JTLV+/frBTtTUKQsSe46YWMB1jqKHsegje44Yxp7ERbYaVbImb5E/yGD6+eeffW5zwQUXiB87o6+QzTCxrXOkHIscVosMxqKPcqwZhrEXPOPZ2DjK4bAaE8PQD3mOuAhkZDGG0dJ5XBnGlvCZaWPjiDKEGCZWoZ8GjwrZfCxGAqOnSIrfGYaxF3xm2hDWHDF2CP3Uk+dINdRZcxQZWJDNMPEBz3g2pKq+QfzlsBoTC+SC3UDZao0cVotuKj8bRwxjR3jGsyE1am0ZbjzLxDaspqtzlM5TRTQ8R5ytxjD2hM9MG8LZaow9wmqsOYo0xjCaMXuNYRh7wGemDamuk9lqcVFpgUlUz5HIVuNU/khiFGBzWI1h7AnPeHb2HGXw18PE1nPERSAjS6pBc2QMszEMYw/4zLQhrDliYomsvSOy1TisFuUK2ew5Yhg7wsaRDanisBpjg4wqzzpHPFVEAhZkM0x8wGemDalhQTZjlwrZ6rHI2WrRKQLJ7UMYxp7wjGczqKwMpVATbBwxscyoot5qdWqdowz2cEQEo6eINUcMY0/4zLQZtcpaJMjmIpBMDDOqFM+RrHPEx2I0UvnZ6GQYe8Jnps1Q1yKR1cJiTSamniNO5Y84xrpG3D6EYewJz3g2Q9ViIyc9FQ4HT5yMXRrP8lQRCVhzxDDxAc94NkPtOYssDqkxMfZuUFiN6xxFFr2niAwjvgBiGHvCueI2NY5YjM3EPqxGniPlNtc5irwgm9P4Gca+8NlpM+qcymKUw54jJkbIRVs0nmXNUUTRh9FYb8Qw9oU9RzbVHHF1bCbWC3ij0wWnSykrwXWOIoM+dZ89RwxjX/jstGm2GofVGDss4KpthMxUPh4jgT4DlcXYDGNf2DiyGbUyW43DakyMMKu9w56jyDeeZc8Rw9gXPjtt6jnibDUmVphpYbhYYTQE2ew5Yhi7wjOezeBsNSbWGMM9ZBilcAgoCoJsnn4Zxq7w2Wkz6ho5W42JLVR7R7+Ic6ZadDxHrDliGPvCs57NYM8RY7fQGheAjBw8rgwTH/DZadcK2WwcMTZoPkuw5yg6vdXYc8Qw9oVnPZsaRxxWY+zi4chkQz06qfysOWIY28Jnp82oV1P5s9k4YmKIfuFmz1G0UvnZc8QwdoVnPZvBmiPGDqTrFnHWxkQO7q3GMPEBn5027a3GniMmlrDnqAlS+XX6I4Zh7AWfnTbtrcaeI8Y2mqM0PhYjBYfVGCY+YOPIrmE19hwxMYSz1aJXQ0oaRSzIZhj7wmenzWDNEWMHuB5P9JDhNPYcMYx94VnPZrDniLEDerEwe46iozvSe+cYhrEXfHbaNJU/Jz0t1rvCJDF6rwZrjqLjlTNr8MswjD1g48hGuFwud4XsDP5qmNihz6TKTOdjMZJIrRGn8jOMfeGz00bUNTjhgprKz5ojxi6aI17Eo1JDijVHDGNfeNazEdX1qtuIjSPGTpoj9hxFxXPE2WoMY1/47LQR1argiK4oeeJk7FKskDVH0fHK6auQMwxjL3gFthHVagVI9hoxsYaz1aKHzFLjCyCGsS98dtrQc8Rp/Iy9KmTzNBGNKtksyGYY+8Jnpx2NI/YcMTbKVsvgsFpEkUJsFmQzjH1h48hGsHHE2LPOEU8TURFks+aIYWwLz3o2okYtcsRhNcZWYTXOVoso0ihizRHD2Bc+O21Eleo5yuLFiLFTEUgOq0UUqTXi+lEMY1/47LQRNapxlMNhNcZGYTVuPBtZjm6dD4cD6N4qL9a7wjCMBdzAy4aaoyw2jpgYw6n80ePvE3vj+tHdUZyXGetdYRjGAp717FjniDVHTIzR62HYOIosKSkONowYxubwrGcjOFuNsQv66s2sOWIYJtlg48hG1Ki91dg4YuzkOWLNEcMwyQbPejaiSg2rcbYaE2u4zhHDMMkMz3p2zFZjzRFjp8azbKwzDJNk8KxnS88RG0eMnQTZfDwyDJNcsHFkQ88Ra46YWMNhNYZhkpm4m/Vqa2sxaNAgOBwOLF261OOx5cuX48QTT0RWVhY6duyIJ5980uv5n376KXr16iW26d+/P6ZMmQLbZatxWI2xU+NZruTMMEySEXez3p133ol27dp53V9eXo6xY8eic+fOWLRoEZ566ik8+OCDeP3117Vt5syZg0mTJuGqq67CkiVLcPbZZ4uflStXwl6p/HH3tTAJ2luNDCOqy8MwDJNMxFWF7O+++w5Tp07F559/Lm7r+eCDD1BXV4c333wTGRkZ6Nu3r/AsPfPMM7jmmmvENs8//zzGjx+PO+64Q/z/yCOPYNq0aXjppZfw6quvWnqq6EdvhBH19fXiJxpFIDNSlNdnooccXx5ncxwup5bGH+4Y8Vg3HTzWTQePdfyNdTDPjxvjaO/evbj66qvx1VdfIScnx+vxuXPnYtSoUcIwkowbNw5PPPEEysrKUFRUJLa57bbbPJ5H29BrWvHYY4/hoYce8rqfjDSz/QiHsnIKpzmwbPEClK2P6EszFpBxzHizopS8RamAsz5ioWce66aDx7rp4LGOn7GuqqpKLOPI5XLh8ssvx7XXXothw4Zh69atXtuUlJSga9euHve1bt1ae4yMI/or79NvQ/dbcffdd3sYVOQ5Ij0ThfAKCgoQSR5YOoNsW5x0wkj0btcsoq/NeF9B0Ik2ZswYpKenx3p3bEfu+v3497olyM/JxoQJo8J6LR7rpoPHuungsY6/sZaRH9sbR3fddZfw7PhizZo1wktz5MgRYag0NZmZmeLHCH1BkT4hahqUsFpBTiafbE1ENL7HRCBL9cBSWYlIjQ+PddPBY9108FjHz1gH89yYGke333678Aj5olu3bvjpp59ESMxopJAX6ZJLLsE777yDNm3aiNCbHvk/PSb/mm0jH48lTqdLax/CdY6YWNO1Za4oBHl067xY7wrDMEyTE1PjqGXLluLHHy+88AL+7//+T/t/9+7dQiv0ySefYPjw4eK+ESNG4N577xXuN2kdkhuuZ8+eIqQmt5k+fTpuueUW7bVoG7o/1kivEcHZakysad8sG/PuORWF2XxFzDBM8hEXmqNOnTp5/J+Xp1zNdu/eHR06dBC3L774YiGcpjT9v/3tbyI9n7LTnn32We15N998M0466SQ8/fTTmDhxIj7++GMsXLjQI90/VshMNSKLKxIzNqBFnnc4mWEYJhlIGBdFYWGh0CZt2bIFQ4cOFSG7+++/X0vjJ0aOHIkPP/xQGEMDBw7EZ599JjLV+vXrB7vUOEpPcXFdGYZhGIaJIXHhOTLSpUsXkcFmZMCAAfj55599PveCCy4QP3ZDX+OIYRiGYZjYwUuxTZCeIzaOGIZhGCa28FJsE+obXcjNSEUmy40YhmEYJqawcWQThnYuwtL7TsVdA93CbIZhGIZhmh42jmyGg7XYDMMwDBNT2DhiGIZhGIbRwcYRwzAMwzCMDjaOGIZhGIZhdLBxxDAMwzAMo4ONI4ZhGIZhGB1sHDEMwzAMw+hg44hhGIZhGEYHG0cMwzAMwzA62DhiGIZhGIbRwcYRwzAMwzCMDjaOGIZhGIZhdLBxxDAMwzAMo4ONI4ZhGIZhGB1p+n8Y/7hcLvG3vLw84q9dX1+Pqqoq8drp6ekRf33GDY9108Fj3XTwWDcdPNbxN9Zy3ZbruC/YOAqSI0eOiL8dO3aM9a4wDMMwDBPCOl5YWOhzG4crEBOK0XA6ndi9ezfy8/PhcDgi+tpk1ZLRtWPHDhQUFET0tRlPeKybDh7rpoPHuungsY6/sSZzhwyjdu3aISXFt6qIPUdBQgPaoUOHqL4Hffl8sjUNPNZNB49108Fj3XTwWMfXWPvzGElYkM0wDMMwDKODjSOGYRiGYRgdbBzZiMzMTDzwwAPiLxNdeKybDh7rpoPHuungsU7ssWZBNsMwDMMwjA72HDEMwzAMw+hg44hhGIZhGEYHG0cMwzAMwzA62DhiGIZhGIbRwcaRTXj55ZfRpUsXZGVlYfjw4Zg/f36sdynueeyxx3DMMceIauatWrXC2WefjXXr1nlsU1NTgxtuuAEtWrRAXl4ezjvvPOzduzdm+5woPP7446KC/C233KLdx2MdOXbt2oVLL71UjGV2djb69++PhQsXao9Tns3999+Ptm3bisdPO+00bNiwIab7HI80NjbivvvuQ9euXcU4du/eHY888ohHby4e69CZPXs2zjjjDFGxmuaLr776yuPxQMa2tLQUl1xyiSgO2axZM1x11VWoqKhAuLBxZAM++eQT3HbbbSJVcfHixRg4cCDGjRuHffv2xXrX4ppZs2aJxfi3337DtGnTRPPCsWPHorKyUtvm1ltvxeTJk/Hpp5+K7ak1zLnnnhvT/Y53FixYgNdeew0DBgzwuJ/HOjKUlZXh+OOPFw04v/vuO6xevRpPP/00ioqKtG2efPJJvPDCC3j11Vcxb9485ObmijmFDFQmcJ544gm88soreOmll7BmzRrxP43tiy++qG3DYx06NBfTekfOATMCGVsyjFatWiXm+G+++UYYXNdccw3ChlL5mdhy7LHHum644Qbt/8bGRle7du1cjz32WEz3K9HYt28fXe65Zs2aJf4/dOiQKz093fXpp59q26xZs0ZsM3fu3Bjuafxy5MgRV48ePVzTpk1znXTSSa6bb75Z3M9jHTn+9re/uU444QTLx51Op6tNmzaup556SruPxj8zM9P10UcfNdFeJgYTJ050XXnllR73nXvuua5LLrlE3Oaxjhw0F3z55Zfa/4GM7erVq8XzFixYoG3z3XffuRwOh2vXrl1h7Q97jmJMXV0dFi1aJNyF+v5t9P/cuXNjum+JxuHDh8Xf5s2bi7807uRN0o99r1690KlTJx77ECFP3cSJEz3GlOCxjhxff/01hg0bhgsuuECEiwcPHow33nhDe3zLli0oKSnxGGvqJ0Xheh7r4Bg5ciSmT5+O9evXi/+XLVuGX375Baeffrr4n8c6egQytvSXQml0Pkhoe1pDydMUDtx4NsYcOHBAxLVbt27tcT/9v3bt2pjtV6LhdDqF/oXCEf369RP30YmXkZEhTi7j2NNjTHB8/PHHIixMYTUjPNaRY/PmzSLUQ6H4e+65R4z3TTfdJMb3sssu08bTbE7hsQ6Ou+66S3SEJ0M+NTVVzNX/+Mc/RCiH4LGOHoGMLf2lCwQ9aWlp4gI43PFn44hJGo/GypUrxVUfE3l27NiBm2++WcT9KamAia6hT1fKjz76qPifPEd0bJMug4wjJnL897//xQcffIAPP/wQffv2xdKlS8VFFgmIeawTGw6rxZji4mJxRWLM2qH/27RpE7P9SiRuvPFGIdSbMWMGOnTooN1P40thzUOHDnlsz2MfPBQ2owSCIUOGiCs3+iHRNYkp6TZd7fFYRwbK3OnTp4/Hfb1798b27dvFbTmePKeEzx133CG8RxdddJHICPzDH/4gEgsoE5bgsY4egYwt/TUmLjU0NIgMtnDHn42jGEOu8KFDh4q4tv7KkP4fMWJETPct3iGNHxlGX375JX766SeRjquHxp0yfvRjT6n+tMjw2AfHqaeeihUrVogra/lD3g0KP8jbPNaRgULDxpIUpInp3LmzuE3HOS0M+rGm0BBpMHisg6OqqkroV/TQxSzN0QSPdfQIZGzpL11w0cWZhOZ6+n5ImxQWYcm5mYjw8ccfCwX+22+/LdT311xzjatZs2aukpKSWO9aXHPddde5CgsLXTNnznTt2bNH+6mqqtK2ufbaa12dOnVy/fTTT66FCxe6RowYIX6Y8NFnqxE81pFh/vz5rrS0NNc//vEP14YNG1wffPCBKycnx/X+++9r2zz++ONiDvnf//7nWr58ueuss85yde3a1VVdXR3TfY83LrvsMlf79u1d33zzjWvLli2uL774wlVcXOy68847tW14rMPLbl2yZIn4IXPkmWeeEbe3bdsW8NiOHz/eNXjwYNe8efNcv/zyi8iWnTRpkitc2DiyCS+++KJYODIyMkRq/2+//RbrXYp76GQz+3nrrbe0begku/76611FRUVigTnnnHOEAcVE3jjisY4ckydPdvXr109cVPXq1cv1+uuvezxOadD33Xefq3Xr1mKbU0891bVu3bqY7W+8Ul5eLo5hmpuzsrJc3bp1c917772u2tpabRse69CZMWOG6RxNRmmgY3vw4EFhDOXl5bkKCgpcV1xxhTC6wsVBv8LzPTEMwzAMwyQOrDliGIZhGIbRwcYRwzAMwzCMDjaOGIZhGIZhdLBxxDAMwzAMo4ONI4ZhGIZhGB1sHDEMwzAMw+hg44hhGIZhGEYHG0cMwzAMwzA62DhiGCZpePvtt9GsWbOovkeXLl3w3HPPRfU9GIaJLmwcMQyTNFx44YWiSSvDMIwv0nw+yjAMk0BkZ2eLH4ZhGF+w54hhmLjB6XTiscceQ9euXYWRM3DgQHz22WfisZkzZ8LhcODbb7/FgAEDkJWVheOOOw4rV660DKstW7YMo0ePRn5+PgoKCjB06FAsXLhQe/zzzz9H3759kZmZKcJlTz/9tMf+7Nu3D2eccYbYF9qnDz74wGufDx06hD/96U9o2bKleI9TTjlFvC/DMPaFPUcMw8QNZBi9//77ePXVV9GjRw/Mnj0bl156qTA8JHfccQeef/55tGnTBvfcc48wXiiUlp6e7vV6l1xyCQYPHoxXXnkFqampWLp0qbbdokWL8Pvf/x4PPvigCMfNmTMH119/PVq0aIHLL79cbEN/d+/ejRkzZojn3XTTTcJg0nPBBRcI4+m7775DYWEhXnvtNZx66qlin5o3bx71MWMYJgRcDMMwcUBNTY0rJyfHNWfOHI/7r7rqKtekSZNcM2bMcNGU9vHHH2uPHTx40JWdne365JNPxP9vvfWWq7CwUHs8Pz/f9fbbb5u+38UXX+waM2aMx3133HGHq0+fPuL2unXrxPvNnz9fe3zNmjXivmeffVb8//PPP7sKCgrEvuvp3r2767XXXgtjNBiGiSbsOWIYJi7YuHEjqqqqMGbMGI/76+rqhPdHMmLECO02eWZ69uyJNWvWmL7mbbfdJkJe7733Hk477TTh5enevbt4jJ5z1llneWx//PHHi0y0xsZG8XhaWpoIxUl69erlFbarqKgQ3iY91dXV2LRpU8hjwTBMdGHjiGGYuICMDII0Re3bt/d4jDRBoRgbFDK7+OKLxWtS2OuBBx7Axx9/jHPOOSdi+9y2bVuhhzIS7ZICDMOEDhtHDMPEBX369BFG0Pbt23HSSSd5PS6No99++w2dOnUSt8vKyoS2p3fv3pave/TRR4ufW2+9FZMmTcJbb70ljCN6zq+//uqxLf1P25I+ibxEDQ0NQpt0zDHHiMfXrVsnBNiSIUOGoKSkRHiYSNDNMEx8wMYRwzBxAWWU/fWvfxVGDGWtnXDCCTh8+LAwWCgLrHPnzmK7hx9+WISxWrdujXvvvRfFxcU4++yzvV6PQlsk3j7//PNFptnOnTuxYMECnHfeeeLx22+/XRg9jzzyiBBkz507Fy+99BL+9a9/iccpXDd+/Hj8+c9/FoJuMoBuueUWj1IBFKqjMB+9/5NPPikMKxJwk6eKDLBhw4Y12fgxDBMEUVU0MQzDRBCn0+l67rnnXD179nSlp6e7WrZs6Ro3bpxr1qxZmiB78uTJrr59+7oyMjJcxx57rGvZsmXa8/WC7NraWtdFF13k6tixo9i2Xbt2rhtvvNFVXV2tbf/ZZ58JATa9V6dOnVxPPfWUx/7s2bPHNXHiRFdmZqZ4/N1333V17txZE2QT5eXlrr/85S/i9el16P0uueQS1/bt25tkzBiGCR4H/QrGmGIYhrEjpOuhmkUUSmM9D8Mw4cBFIBmGYRiGYXSwccQwDMMwDKODw2oMwzAMwzA62HPEMAzDMAyjg40jhmEYhmEYHWwcMQzDMAzD6GDjiGEYhmEYRgcbRwzDMAzDMDrYOGIYhmEYhtHBxhHDMAzDMIwONo4YhmEYhmHg5v8BMauHZ+eaDooAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True, render_mode=\"rgb_array\")\n",
    "return_history = []\n",
    "\n",
    "alpha_critic = 1e-4\n",
    "alpha_actor = 1e-5\n",
    "gamma = 0.99\n",
    "nb_episodes = 500\n",
    "max_episode_len = 500\n",
    "\n",
    "critic_optimizer = torch.optim.Adam(critic.parameters(), lr=alpha_critic)\n",
    "actor_optimizer = torch.optim.Adam(actor.parameters(), lr=alpha_actor)\n",
    "\n",
    "for j in tqdm(range(nb_episodes)):\n",
    "\n",
    "    accumulated_rewards = 0\n",
    "    state, _ = env.reset()\n",
    "    gamma_k = 1\n",
    "    if j%200 == 0 and j!=0:\n",
    "        max_episode_len+=100\n",
    "    for _ in range(max_episode_len):\n",
    "        next_state, reward, done, action, mu, sigma = interact(\n",
    "            state=np.reshape(state, (1, -1)),\n",
    "            policy=actor,\n",
    "            deterministic=False,\n",
    "            featurizer=featurizer\n",
    "        )\n",
    "        accumulated_rewards += reward\n",
    "\n",
    "        delta, _ = learn_critic(critic, critic_optimizer, state, next_state, done, gamma, featurizer)\n",
    "        _ = learn_actor(actor_optimizer, action, mu, sigma, delta, gamma_k)\n",
    "\n",
    "        gamma_k = gamma * gamma_k\n",
    "        state = next_state\n",
    "\n",
    "        if done:\n",
    "            break\n",
    "\n",
    "    if j % 100 == 0 and j != 0:\n",
    "        plt.plot(return_history, label='Return')\n",
    "        plt.plot(pd.Series(return_history).rolling(10).mean(), label='MA')\n",
    "        plt.xlabel('episode')\n",
    "        plt.ylabel('return')\n",
    "        plt.grid(True)\n",
    "        _ = plt.legend()\n",
    "        plt.show()\n",
    "    return_history.append(accumulated_rewards)\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-cff391e6a4178b47",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "Plot the learning curve of the training process!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-ed5ed20c7c3d4932",
     "locked": false,
     "schema_version": 3,
     "solution": true,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(return_history, label='Return')\n",
    "plt.plot(pd.Series(return_history, name='reward_history').rolling(10).mean(), label='MA')\n",
    "plt.xlabel('episode')\n",
    "plt.ylabel('return')\n",
    "plt.grid(True)\n",
    "_=plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-41b8edc65ba40233",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    }
   },
   "source": [
    "## Execution\n",
    "\n",
    "Use `deterministic` to choose between deterministic execution (apply $\\mu$) directly or take the stochastic action by sampling from the normal distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "nbgrader": {
     "grade": false,
     "grade_id": "cell-d7232e344bf16559",
     "locked": true,
     "schema_version": 3,
     "solution": false,
     "task": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d6d91c5cf4a84eb098933a761b70f2f6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/10 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode 0, Total Reward: 252.21866609956308\n",
      "Episode 1, Total Reward: 229.83386771422292\n",
      "Episode 2, Total Reward: 248.94280970239058\n",
      "Episode 3, Total Reward: 219.42525538714486\n",
      "Episode 4, Total Reward: 236.977106615966\n",
      "Episode 5, Total Reward: 220.67673710388408\n",
      "Episode 6, Total Reward: 252.52566973617206\n",
      "Episode 7, Total Reward: 252.89781479402038\n",
      "Episode 8, Total Reward: 258.05350378806247\n",
      "Episode 9, Total Reward: 233.62832367884394\n"
     ]
    }
   ],
   "source": [
    "env = gym.make(\"LunarLander-v3\", continuous=True, render_mode=\"human\")\n",
    "deterministic = True\n",
    "\n",
    "for j in tqdm(range(10)):\n",
    "    state, _ = env.reset()\n",
    "    accumulated_rewards = 0\n",
    "\n",
    "    while True:\n",
    "\n",
    "        with torch.no_grad():\n",
    "\n",
    "            next_state, reward, done, action, mu, sigma = interact(\n",
    "                state=np.reshape(next_state, (1, -1)),\n",
    "                policy=actor,\n",
    "                deterministic=deterministic,\n",
    "                featurizer=featurizer\n",
    "            )\n",
    "\n",
    "        accumulated_rewards += reward\n",
    "        state = next_state\n",
    "\n",
    "        if done:\n",
    "            print(f\"Episode {j}, Total Reward: {accumulated_rewards}\")\n",
    "            break\n",
    "\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Create Assignment",
  "kernelspec": {
   "display_name": "RL_course_py12",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
